What are your favorite novels featuring scientists? (updated)

In a recent post, we came up with a great list of popular science books that appeal to scientists. Now let’s do the same thing for fiction. What are your favorite novels featuring scientists? I’ll accept novels about academia too.

I’ll kick things off with four very different but equally-excellent selections:

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Recommendations of popular science books that scientists would enjoy? (UPDATEDx2)

I like to read about science and scientists. I like books that get me thinking about science and how to do it. But I find it difficult to identify popular science and history of science books that I will enjoy. The problem is that I’m a scientist. Many popular science books are too basic/slow-moving for me, too familiar, or else too wildly speculative.*

That’s where you come in. In the comments, please share your recommendations for your favorite popular science and history of science books. Specifically, ones that you think that scientists would especially enjoy.

To kick things off, here are some of my favorite popular science books, books that I think readers of this blog would really like as well. I also threw in a book you’d probably think I would’ve liked, but I didn’t.

(UPDATE #2: You have GOT to read the comments as well. Our commenters came through big time, as they always do. I love our commenters!)

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Book review: How the Hippies Saved Physics

Yes, it’s another of my patented non-timely book reviews. At the long-ago suggestion of frequent commenter Jeff Ollerton Artem Kaznatcheev, I just read David Kaiser’s How the Hippies Saved Physics. Here’s my review, which as usual is less about the book and more hopefully-interesting thoughts inspired by the book.

Yes, I know this is useful to like minus-seven of you. Whatever. If all our posts were useful, you’d forget how useful the useful ones are. You’d get tired of winning reading useful posts.* 🙂

tl;dr: It’s a fun and thought provoking book, you should totally read it. Click through if you care why I say that, or if you want to read my half-baked thoughts on the non-tradeoff between creativity and rigor in science, the challenges of pursuing theory-free research programs, and whether there’s really such a thing as a “productive mistake”.

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Brief book reviews: four novels featuring scientists (UPDATE)

A long while back I linked to a list of novels* featuring realistic scientists as central characters, taking place in realistic settings (as opposed to speculative sci-fi). I picked out a few to read, here are my brief reviews.

My hope is that I’m adding a bit of value by reviewing these from my perspective as a scientist, thereby helping you avoid reading stuff that would only work for a non-scientist. What’s plausible to a non-scientist might well be implausible to a scientist.

Warning: mild spoilers ahead for the last book on the list.

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Book review: Lab Coats in Hollywood by David Kirby

A while back I read Lab Coats in Hollywood: Science, Scientists, and Cinema by David Kirby. It’s about how scientific consultants shape the portrayal of scientists and science in Hollywood movies, and how the movies feed back to affect public perceptions of science and occasionally even the direction of science itself. Here’s my review. Links to other reviews here.

tl;dr: If you like movies, like science, and and are all curious about how science ends up on screen, you need to read this book. It’s a lot of fun, and you’ll learn something.

Author David Kirby knows whereof he speaks. He holds a Ph.D. in molecular evolution from the University of Maryland, but left a tenure-track biology professorship to retrain in science and technology studies at Cornell. He’s now a senior lecturer in science communication at the University of Manchester. And as background research for the book, he appears to have spoken at great length to every scientist who’s ever advised on a Hollywood film, and to every filmmaker who’s ever hired a science consultant. Ok, not really.* But I’ve never read a book that packs in so many examples to illustrate its points.

Those examples are the biggest strength of the book. They’re entertaining—Kirby dug up scads of great anecdotes, about films ranging from Contact to Finding Nemo to The Nutty Professor.** They’re fascinating—I loved learning about all the little decisions and moving parts that go into making a movie. They’re organized—Kirby doesn’t just string together anecdotes, he’s got a sensible framework in which they all fit. And they’re informative—the book disabused me of my over-simplified view of how science feeds into Hollywood movies.

Some of big takeaways of the book for me:

  • It’s often said that the need to make a film entertaining ultimately trumps scientific realism. That was my view before I read the book, and at some level it’s true. But that broad-brush picture is tremendously oversimplified. “Entertainment” is an umbrella term for a huge range of considerations—everything from the difficulty of filming people on a dark comet in Deep Impact, to the boring sound that a “realistic” extraterrestrial signal in Contact would actually make, and so on. There are so many judgement calls, so many moving parts, and so many difficult tradeoffs involved in filmmaking!
  • That broad-brush picture also misses the rich cinematic possibilities created by scientific uncertainty, and the complex challenges created by what scientists think is true vs. what the general public thinks is true. For instance, Jurassic Park succeeded in part by pushing back against what was at the time the common public image of dinosaurs as slow, dumb, tail-dragging reptiles. What films need isn’t necessarily to be realistic, or even necessarily to be seen as realistic because they’re consistent with what the general public thinks is true. What they need is to be plausible, and that’s a more complicated notion than you might think. For instance, the Hulk isn’t plausible in any ordinary scientific sense. But there is absolutely is such a thing as a more or less plausible explanation for the Hulk, in the context of the narrative and themes of Ang Lee’s Hulk.
  • Following on from that last remark: films, and filmmakers, vary in their goals. A treatment of science that would work in one sort of movie might not work in a different sort of movie–or even in a seemingly-identical sort of movie! Kirby makes this point by contrasting the treatment of science in different Hulk movies, and in different asteroid/comet-based disaster movies.
  • Science consultants vary, in all sorts of ways. In what they’re asked to advise on (their job is not just to check accuracy in most cases). In their reasons for consulting. In what scientific matters they’re prepared to compromise on. And more. In general, the science consultants who are most successful seem to be the ones who understand what filmmakers are trying to do. Who help filmmakers overcome constraints and spot opportunities, rather than just trying to impose constraints by saying “that’s not realistic”. The most successful science consultants also seem to be the ones with a healthy sense of what battles to pick. Paleontologist Jack Horner, who consulted on Jurassic Park, is a good example here. He’s sensible enough to realize that a movie that puts evolution front and center (by making “birds are dinosaurs” a central theme), and that portrays paleontology as an exciting career and paleontologists as brilliant heroes, is a godsend for science. In contrast, it doesn’t matter one whit for public understanding of science that Jurassic Park gave Dilophosaurus a neck frill it didn’t actually have. (If you as a scientist insist on worrying about some aspect of the science in Jurassic Park, worry about how it reinforces the popular notion that genetic engineering is inherently dangerous.)
  • Filmmakers don’t get enough credit from scientists for the details they get right, relative to how much they get ripped for the details they get wrong. Did you notice how Russell Crowe writes equations in A Beautiful Mind? Probably not—which means the filmmakers did their job. If you’d noticed, it would’ve been because the writing somehow looked “wrong”. As soon as viewers notice that sort of thing, they become conscious that they’re watching a movie, rather than just watching the movie. Which is why the filmmakers employed a real mathematician as a hand double to write the equations.
  • All sorts of behind the scenes stuff you’ve probably never thought about. Like what determines who gets to be a science consultant. It’s often less about your expertise and more about “Can you spend a month on set in LA?”

Here are a couple more teasers from the book, to encourage you to read it:

  • Kirby begins the book with an extended discussion of the Hollywood film that paid much more attention to scientific realism than any movie before or since. Try to guess it in the comments!
  • You’ll have to read the book to find out what caused Ang Lee to say to his science consultant, “So, Hulk is a plant?” 🙂

I liked that the book isn’t overstated. Kirby doesn’t overrate the importance of his subject, noting that it’s hard to identify any movie that suffered at the box office because of its portrayal of science. I do think Kirby slightly overrates the effect that movie science has on science funding and science policy. I think he may be overgeneralizing from a few exceptional cases. I also think he slightly overrates the potential for movies to affect debates among scientists. Yes, there are scientists who’ve been quite keen to get their pet hypotheses into films: Jack Horner in Jurassic Park, fringey geophysicist J. Marvin Herndon in The Core, others. But that doesn’t imply that those films actually affected internal scientific debates in any important way, and Kirby doesn’t suggest any mechanism by which they could’ve done so. I suspect the hypothesis that birds are dinosaurs would’ve won the day in scientific circles, and done so just as fast as it actually did, even if Jurassic Park had never been made, or had had an opponent of the hypothesis as its scientific consultant. But that’s just a gut feeling on my part, I could be wrong.

In summary, Lab Coats in Hollywood is worth your time, I recommend it.

*As an ecologist, you might be a little disappointed that Kirby has very few examples involving ecology–Finding Nemo is the only one I recall. I was curious if any ecologists consulted on Avatar, but that movie doesn’t come up.

**Yes, The Nutty Professor had science consultants. You’d be surprised at some of the films that did.

Book review: Theory and Reality: An Introduction to Philosophy of Science by Peter Godfrey-Smith (UPDATED)

In a recent post on philosophy of science for ecologists, Brian identified Harvard philosopher Peter Godfrey-Smith’s Theory and reality: an introduction to the philosophy of science as promising-looking. I thought it looked promising too, so I read it (Kindle edition). Here’s my review. (UPDATE: another review here)

The book is based on introductory lectures in philosophy of science that Godfrey-Smith used to give at Stanford. It assumes no background knowledge of philosophy, and so is perfectly accessible to anyone reading this blog. But it’s aimed at people interested in philosophy, and takes that interest for granted. It doesn’t spend much time trying to argue you into an interest in philosophy you don’t already have. And it’s not aimed at teaching you just the bits of philosophy of science that you need to know in order to be a good scientist, or a better scientist than you are already. For instance, at various points it links philosophy of science to topics in epistemology and metaphysics that scientists have no particular reason to care about. So it’s not the philosophical equivalent of, say, an introductory biostats course or “math for ecologists” or whatever. Whether you find philosophy of science useful in your day-to-day scientific work is up to you.* But if you want to have a better sense of where philosophers of science are coming from, and be able to identify and understand those bits of philosophy of science that are relevant to you as a scientist, then I think you’ll find this book very helpful.

The first 2/3 of the book is a chronological survey of the most important work in philosophy of science from the early 20th century up until almost the present day, with a few nods to important earlier figures. It switches from chronological to topical organization to cover recent work. I think the chronological organization is effective. Features of later work that might otherwise seem puzzling make more sense when you know about the earlier work that later work was either trying to build on or improve upon. The book also includes a couple of chapters on fields on the boundary of philosophy of science (sociology of science, and feminist philosophy of science and “science studies”).

It’s a short and easy read—I knocked it off in a couple of days. It’s the philosophy of science equivalent of one of those bus tours that takes you to, say, Westminster Abbey, the Palace of Westminster, Tower Bridge, the Tower of London, St. Paul’s Cathedral, Stonehenge, and Bath all in one day. Yes, those bus tours only hit the obvious highlights, and yes they only give you a quick superficial glance at the sights you’re seeing, and yes they leave you wanting to go back for more. But they fill a real need. So for “Westminster Abbey, the Palace of Westminster…” read “the logical postivists, Hempel, Quine, Popper, Kuhn, Lakatos, Feyerabend, Laudan, Goodman,” plus various other figures discussed more briefly.

It’s an opinionated survey. Godfrey-Smith always tells you what he thinks of the ideas he discusses, and he uses the final chapters in part to lay out and stump for his own views. I welcomed this. I wouldn’t want a he-said, she-said survey that just describes what philosophers have written without any attempt at evaluation. Reading someone else’s evaluation helps me form my own evaluations, rather than getting in the way of me forming my own evaluations. Especially since Godfrey-Smith always gives a fair (sometimes generous) description before he launches into (often critical) evaluation. Nor does he skip any major ideas he disagrees with. At least, I didn’t notice any obvious gaps in the coverage, and I know enough philosophy that I’m fairly sure I would have. And Godfrey-Smith tells you when his own views are unorthodox, as opposed to when he’s voicing widely-shared opinions, so he never comes off as trying to railroad you towards his own views.

I broadly agree with Godfrey-Smith’s views, and I think most scientists will too. He’s a “naturalist”, which in this context means a philosopher of science who takes as his starting point how actual (rather than hypothetical or idealized) scientists go about their business. (Not that he thinks science as its currently practiced is above criticism, including philosophical criticism.) The only point where I seriously disagreed with him was his explication of subjective Bayesianism, which is surprisingly light on criticism. Godfrey-Smith strongly criticizes many other views, his overall judgement seems quite good, and he’s familiar with current everyday scientific practice. So I don’t understand how he could fail to strongly criticize a view that has been strongly criticized by various recent philosophers of science (e.g., Deborah Mayo), and that has never gotten any traction among practicing scientists or statisticians.** Especially because the subjective Bayesian view grew in part out of Carnap’s work in logical positivism, and Godfrey-Smith follows the rest of philosophy of science in writing off Carnap’s work as a dead end.

For those of you who worry that philosophy of science is remote from the actual practice of science, well, if your read this book you’ll discover that many philosophers of science worry about that too. As the book discusses at length, perhaps the biggest issue in philosophy of science ever since Thomas Kuhn’s Structure of Scientific Revolutions in 1962 has been figuring out the philosophical implications, if any, of how science was and is actually done. Those implications aren’t obvious. There’s an old philosophical dictum, dating back at least to Hume, that “is does not imply ought”. That is, descriptive and normative issues are two different things. How scientists do science, or how they’ve done it in the past, doesn’t on its own imply anything about how science should be done (especially since scientists themselves often disagree with one another on how to do science). But on the other hand, the descriptive and normative aren’t totally independent of one another either. As another old philosophical dictum goes, “ought implies can”. That is, any claim about how things should be presupposes that they could be that way. I have to say that I sometimes found Godfrey-Smith a bit unclear on the relationship between descriptive and normative claims in philosophy of science. Or maybe just a bit unclear on what claims are being made in the first place. In particular, some (not all) recent work at the interface of philosophy of science and other disciplines—sociology of science, “science studies”, feminist philosophy—arguably suffers from muddying descriptive and normative claims, and from lack of clarity about exactly what’s being claimed in the first place. Godfrey-Smith notes this, but his summaries of this work sometimes suffer a little from the same flaw, I think. In his admirable urge to take seriously recent work at the boundary of philosophy of science and other disciplines, I think he’s a bit less critical and demanding of that work than he should be. For instance, there’s a serious discussion of Bruno Latour, whom Andrew Gelman for one frequently mocks, and not without reason. I don’t think Godfrey-Smith should’ve mocked or omitted Latour and related figures. But I do think the chapters on sociology of science and feminism/science studies are a bit too uncritical and drift a bit too far away from philosophy of science sensu stricto. And Godfrey-Smith’s explication of his own naturalism wasn’t totally satisfying to me. I left the book with more of a sense of what his naturalism isn’t than what it is. Bill Wimsatt is one naturalist philosopher of science who’s good at linking how science is actually done to a normative account of how it should be done. For instance, Wimsatt emphasizes how human beings are cognitively limited in all sorts of ways. Many scientific practices involve heuristics and “rules of thumb” that would be suboptimal or even undesirable for a cognitively-unlimited being, but that are optimal given humans’ cognitive limitations. The scientific preference for “simple” or “parsimonious” models is a good example. As Godfrey-Smith notes, philosophers of science have tried mightily—and failed abysmally—to find a universal justification for preferring simple models. After all, the truth might be complicated. And there doesn’t seem to be any other desirable property (testability or whatever) that invariably increases with the simplicity of one’s model. But as Wimsatt (but not Godfrey-Smith) notes, real scientists’ preference for simple models doesn’t have the sort of universal justification philosophers traditionally have sought. Rather, a preference for simple models is justified in many contexts (not all!) for heuristic reasons, such as that real human beings just can’t wrap their heads around complex models, and that simple models often (not always!) provide a good-enough approximation to more complex models.

At the end of every chapter are suggestions for further reading, along with brief comments (e.g., identifying which of the readings are accessible and which are advanced and technical). This is very helpful. There’s also a glossary, which I didn’t really need since I’ve read some philosophy of science already, but which I imagine would be a godsend for someone totally new to the subject. And while we’re on the subject of vocabulary,Godfrey-Smith is good about alerting the reader to (and avoiding) loaded terms that get used in different ways by different philosophers.

The style is clear and readable. There are occasional jokes, often rueful apologies for using well-worn examples. And the book shows its origins as introductory undergraduate lectures in a good way. Godfrey-Smith is good at picking clear examples to illustrate broader points. And he’s good at picking examples that undermine your pre-philosophical intuitions, and so motivate you to stop and think about something that might’ve otherwise seemed obvious.

I took away from the book a better understanding of some philosophical topics that I previously hadn’t understood. For instance, going into the book I’d found Nelson Goodman’s notion of “grue” to be weirdly pointless. I stand corrected on that, at least in part. I now see the point of “grue”, and it was interesting to find that it’s actually scientifically relevant (although I still think Goodman did himself no favors by making his point with such a weird hypothetical***). And I really like Godfrey-Smith’s own resolution of the “grue problem”. I now have a better understanding of Kuhn, including the various tensions and ambiguities in Kuhn’s thought. And I have a better sense of the current lay of the land in philosophy of science.

I’d recommend the book to anyone who wants a quick accessible overview of philosophy of science, including scientists who want an overview so that they can then hone in on the bits of philosophy of science most relevant to their own work.

*At least in part. It might also depend on the state of your field—you might have no choice but to learn and do some philosophy of science. Godfrey-Smith discusses the possibility that philosophical issues loom large for practicing scientists only under certain circumstances, such as during Kuhnian “paradigm shifts”. I think this is right. Part of why I’m interested in philosophy of science is that I think philosophical issues loom larger in a young field like ecology than they do in, say, chemistry.

**“Bayesian” scientists and statisticians come in various stripes, but hardly any are subjective Bayesians in the sense Godfrey-Smith explicates, and most would find that sort of subjective Bayesianism totally bizarre. Andrew Gelman, for instance, is a self-described Bayesian, but is emphatically against the sort of subjective Bayesianism philosophers of science apparently have paid the most attention to.

***And I say that as someone who very much sees a place for ridiculous hypotheticals.

Book review: The Bet by Paul Sabin

For Christmas my brother-in-law gave me The Bet by Paul Sabin. Here’s my review. You can find other reviews by googling.

Sabin is a history professor at Yale. The Bet is a popular (but fully footnoted and sourced) account of a famous bet between ecologist Paul Ehrlich and economist Julian Simon over whether the real (i.e. inflation-adjusted) prices of five widely-used metals would rise or fall over the 1980s. Ehrlich thought they would rise because human population growth would lead inexorably to resource scarcity. Simon thought they would fall because the combination of free markets and human ingenuity would lead to the development of either new sources or substitutes. Simon won. Sabin places the bet in the context of the US environmental movement of the 60s and 70s, particularly concern about overpopulation, and the subsequent conservative pushback. At the end, he argues that both Ehrlich and Simon, and the movements they helped inspire and lead, failed to appreciate the good points of the other side. Instead, the political debate became too personal, polarized, and extremist to be useful. This degraded the ability of the American government to address serious environmental problems, including climate change, and degraded the ability of American society to have a serious conversation about what sort of world we want to live in.

I liked the book and recommend it. It’s a quick read—I knocked it off in a few hours. It’s engaging—lots of personal background and anecdotes about Ehrlich and Simon.* And I learned a lot. I came into the book knowing only the broad-brush potted history of the environmental movement, and Ehrlich’s role in it.** But while I now know more, the fact that I don’t have many other sources to draw on besides The Bet means that I’m not well-positioned to identify any serious flaws in it. So take everything I say with a grain of salt.

Some hopefully-interesting thoughts inspired by the book:

  • As with any history book, part of the fun is putting yourself in a different mindset. Hard as it may be to believe now, a few decades ago human population size was well under half of what it is today–and yet human population growth was one of the big issues of the day.
  • I came into the book with the vague sense that Ehrlich was basically right (or at least closer to right than Simon was), that he was unlucky to lose the bet, and that events like east African famines illustrate Ehrlich’s basic rightness. I left it thinking that Ehrlich was basically wrong. Ehrlich’s claims were much more specific and extreme than just “humans are having a big effect on the planet and this creates some serious problems that we need to address”. Of course, Simon had his own blind spots, especially as his own position grew more extreme (and frankly, odd). I like Cass Sunstein’s characterization of the Ehrlich-Simon clash as “a clash of two hedgehogs“. If you want to think sensibly about human population growth and its consequences, I think you’re much better off with Joel Cohen’s How Many People Can the Earth Support? than with anything by Ehrlich or Simon.
  • I myself have dealt in a small way with the same problem faced by Ehrlich, Simon, or any activist. To get people to pay attention to what you have to say, you often have to say it in an attention-grabbing way. In my case, by making zombie jokes. But the same rhetoric that gets people’s attention also can make them less likely to agree with you.
  • You can’t always map in any simple way from someone’s experiences growing up to their professional views as adults. But in this case, it sounds like you can (assuming that Sabin isn’t slanting the biographical material in order to jam Ehrlich and Simon into tidy boxes). Ehrlich always loved butterflies and lonely wilderness, and was viscerally repulsed by the crowded cities he visited in India. In contrast, Simon always liked the bustle of city life. I suspect this is what a lot of heated debates, in and outside science, come down to—disagreements about deep-seated preferences and values. Witness the current fight in conservation biology over whether we should conserve nature for its own sake, or for our sake—it’s a fight even among people who agree that nature should be conserved! It’s really hard to have a productive discussion about deep-seated values, or to have a political process that functions well despite the participants disagreeing deeply about values. Which is why I was disappointed in Sabin’s call at the end for a nuanced debate about how humans should live in a world with rapid anthropogenic climate change. He sounds like he’s wishing for a pony, because he doesn’t say anything about how one might create (recreate?) the conditions under which an urgent debate is possible without getting dominated by extreme voices. Easy for me to talk, of course, since I don’t have an answer here either.
  • I was interested to read quotes from Ehrlich and his collaborators saying explicitly that their goal wasn’t to win a reasoned argument. The goal was to use any means necessary—including “alarmism” (their word) and insulting their opponents—to attract attention, set the political agenda, and change government policy. Obviously, there are lots of ways for scientists to get involved in politics besides Ehrlich’s way. But if you want to know what it looks like for a scientist to go “all in” in pursuit of a policy goal, read this book and find out.
  • It’s striking that Ehrlich and Simon both tried to bolster their political position by claiming that objective science was totally on their side, and that the other side was just ignorant of basic, obvious “facts”.
  • At one level, the bet was pointless—the outcome was never going to prove anything about the consequences of human population growth. On the timescale of a decade (or even much longer), commodity prices in both nominal and real terms depend totally on macroeconomic forces, not on human population growth (which is why the fact that Ehrlich would’ve won the bet in the majority of other 10-year periods for which we have data is irrelevant). But on another level, the bet does illustrate that Ehrlich was wrong. Timescales and timing matter. Foreseeing global famine and worldwide collapse of human society within, say, a couple of decades is very different than foreseeing them, say, centuries from now. And it’s not helpful to predict a global disaster at some indeterminate point in the future, as Ehrlich did in the aftermath of the bet. In the long run we’re all dead. Yes, insurmountable physical or biological constraints of some sort will bite at some point—Simon’s later claim that the human population could keep growing exponentially for 7 billion years is silly, there’d be more humans than atoms in the universe at that point. But saying “Some insurmountable physical or biological constraint will bite at some point” is no guide at all to policy—it’s far too vague, except perhaps as an added reason to undertake policies that would be a good idea anyway. And saying “I’m still right, my prediction just hasn’t come true yet” is just a way of absolving yourself from admitting error.
  • I have an old post extolling the value of betting your beliefs, on the grounds that bets force you to be precise and explicit. Thereby removing your wiggle room to rationalize and obliging you to recognize your mistakes and thus learn from them. That may work in contexts where people aren’t personally invested in the outcome of the bet. But as the aftermath of the Ehrlich-Simon bet illustrates, nothing can make a true believer admit error and give up his core beliefs, especially not when doing so would only hand a further political victory to his opponents. Ehrlich paid out on the bet—but subsequently claimed that the bet was on matters of “marginal importance”, and that he was “schnookered” into taking the bet in the first place (no he wasn’t). And his collaborator John Holdren claimed that he and Ehrlich were never making predictions and so it didn’t matter if they were right or wrong. Rather, they were merely raising possibilities (never mind that, if you’re merely raising possibilities, you don’t bet on them coming true.)***
  • It’s telling that Ehrlich and Simon tried and failed to agree a second bet. Ehrlich wanted a new bet on trends in environmental variables like atmospheric CO2 concentration and tropical forest area, while Simon wanted to bet on trends in variables directly related to human health and wellbeing, like life expectancy. Their failure to agree a second bet nicely illustrates that what was always at stake here was values, not empirical claims.
  • Human population growth apparently was the issue for Ehrlich, but it was interesting to read about how he ended up taking stances on lots of other issues too, based on purported links to human population growth. For instance, he got into a lot of political trouble arguing that the US should severely restrict or eliminate immigration, because immigrants to the US would consume resources at the high per-capita rates typical of Americans. This was interesting to me, because it contrasted with my mental image of people with a single-issue focus as not caring about other issues. Single-issue politics of Ehrlich’s sort has two obvious drawbacks as a political approach. First, you have to convince people that one issue really is of overriding importance, so that it should dictate our stances on all other issues. That seems difficult except in wartime. This is well illustrated by Ehrlich’s fight with fellow environmentalist Barry Commoner over whether human population growth was even an issue at all. Second, you end up picking counterproductive fights with people who don’t agree with your stance on other issues. I think the same points crop up in other contexts, including scientific ones (e.g., some debates over open access publishing).
  • On the other hand, in highlighting the downsides of Ehrlich’s approach to politics, I wonder if Sabin isn’t missing some things. For instance, if you really do think human society faces an imminent existential threat and that the only chance of survival is to make all sorts of radical policy changes, then it makes sense to try to maximize the (necessarily small) chance of making those radical changes happen. And even if your goal is more incremental policy change, there might be times when getting incremental change means arguing for radical change. Perhaps in order to reach the sky, you have to aim for the stars. Sabin notes that environmentalism in the 1970s had a lot of big political successes, but at the end he kind of implies that those successes could’ve happened without folks like Ehrlich taking radical stances. I’m not sure. For instance, what if radicals widen the Overton window, the range of possible policies that get seriously considered rather than dismissed out of hand? By publicly discussing extreme policies****, radicals might widen the Overton window. There’s a fine line to walk here, obviously—advocate for something too extreme and you risk getting dismissed as a nutter and making less-extreme views also seem nutty by association, narrowing the Overton window rather than widening it. But obviously, it’s really hard to do counterfactual history and say how much political success the environmental movement would’ve had in the 1970s with a different mix of political tactics.

I bet (haha) that many of you also have read The Bet, or haven’t but have interesting thoughts nonetheless. Looking forward to reading your comments.

*The coolest of which was learning that it was Julian Simon’s idea to have airlines offer money to passengers who volunteered to be bumped from overbooked flights. Previously, they used to just bump people involuntarily.

**Just as an aside, I’ve never met or corresponded with Ehrlich or anyone else who crops up in the book.

***Of course, as Noah Smith points out, people might take a bet for all sorts of reasons besides their beliefs about whatever that particular bet is about. So while Sabin thinks that Ehrlich was sincerely betting his beliefs, one could certainly imagine him taking the bet for other reasons instead of or in addition to that. Say, as just one more way of attracting media attention.

****For instance, Ehrlich refused to rule out the possibility of mass forced sterilizations (!), though he stopped short of arguing for them.

Brief book reviews: The Science of the Struggle for Existence, Darwinian Populations and Natural Selection, and Why Do Lemmings Commit Suicide? (UPDATED)

This post is an experiment. It’s brief reviews of three older books that I think will be of interest to many of you, but that I suspect many of you weren’t aware of. My goal is to say just enough to help you decide whether or not to add these books to your reading list.

The Science of the Struggle for Existence by Gregory Cooper. So, what is ecology, anyway? How is it related to other fields, like evolutionary biology? Does ecology have laws? What cognitive role does theory play in ecology, and how is that role different than the role theory plays in other fields like physics? Philosopher Gregory Cooper sets out to address those questions and more. I don’t know that he’s entirely successful. Much of the book seemed to comprise throat-clearing. Cooper spends a lot of time briefly raising issues only to set them aside with a promise to return to them later. He also spends a lot of time worrying over definitions. Indeed, the book is structured around a–ultimately only semi-successful–search for the definition of ecology, in the hopes that once a definition is in hand light can be shed on conceptual issues and debates within ecology. And Cooper recognizes this, as he takes great pains to explain why he structured the book as he did, and periodically apologizes for spending yet more time on preliminaries. The result is a book that was kind of rough sledding for me, though probably a philosopher would find it easier going. The strengths of the book include the second chapter, which is an excellent potted history of ecology that I recommend to any graduate student. And near the end of the book all the preparatory remarks start to pay some dividends, as Cooper sheds some light on the value of theory in ecology. The main take-home point is that there can be genuine theoretical explanations in ecology even though there are no laws in ecology (if you want elaboration, read the book!) (UPDATE: In the comments, philosopher Chris Eliot suggests–quite fairly–that this may not be the best one sentence summary of Cooper’s take home point. I admit I struggled to come up with a pithy summary…) At the end, I was left with the feeling that Cooper could’ve made the points he wanted to make more briefly and directly. But maybe that’s at least partially ecology’s fault rather than Cooper’s fault. A few years ago, I attended a seminar at Calgary by a leading philosopher of science. After her talk, I asked her why philosophers of science didn’t talk more about ecology. She replied “Because ecology is a mess.” Other reviews (both from philosophers, and both more positive than mine) here and here.

Darwinian Populations and Natural Selection by Peter Godfrey-Smith. Very much at the interface of evolutionary biology and philosophy. Godfrey-Smith, a philosopher at Harvard, looks at how standard idealizations in philosophy of evolutionary biology–and indeed, in evolutionary biology textbooks–need to be modified and extended to account for the diversity of the natural world. For instance, how do you think about group vs. individual selection if individuals aren’t solitary but don’t really live in well-demarcated groups either? What if individual organisms themselves aren’t well-defined? How should one think about “low fidelity” mechanisms of heredity? It’s an attempt to get away from an overly-narrow focus on clear-cut, textbook examples, while maintaining and building on core Darwinian insights (Godfrey-Smith is no fan of alternative paradigms like symbiogenesis) and still fitting everything into a unified framework. I enjoyed the book and learned a lot from it–it really does provide a fresh perspective on some long-standing issues in both biology and philosophy of biology. I’m now clearer about things like “evo-devo” than I was before. It also calls philosophical attention to some new issues. And it’s a clear, easy read (very much in contrast to Cooper’s book in that respect, at least for a non-philosopher like me). The only really weak bit to my mind was the bit where Godfrey-Smith basically does armchair pyschoanalysis on gene selectionists like Richard Dawkins. Sorry, but as someone who wants to understand evolution, I don’t care about Richard Dawkins’ (or anyone’s) psychology and don’t see why I should. Other reviews here and here.

Do Lemmings Commit Suicide? Beautiful Hypotheses and Ugly Facts by Dennis Chitty. This is eminent population ecologist Dennis Chitty’s scientific autobiography, describing his career-long search for the explanation for cyclic population dynamics of small mammals. It’s unusual for scientific biographies, in that it’s a chronicle of admitted failure. Throughout the book, Chitty emphasizes how he kept running into dead ends, kept rejecting one hypothesis after another to explain small mammal cycles, until at the end he’s left without any answers. Chitty also is unusually explicit about his philosophy of science–his attitude towards theory, observations, and experiments, how he decided exactly what projects to pursue and why, etc. I think those two aspects of the book–Chitty’s admitted failure to answer the big question he set out to ask, and his philosophy of science–are closely connected. As the subtitle of the book hints, Chitty has a sort of hard-nosed empiricist mindset. He’s skeptical of mathematical models unless they’ve been tested empirically, and he’s quick to reject models if they don’t pass a test. The trouble is that he’s often too quick to reject hypotheses on the basis of evidence that shouldn’t be taken as decisive. Chitty often seems to be looking for necessary and sufficient conditions for population cycles, or some causal sequence of events that reliably occurs every time a small mammal population crashes and then recovers. Make no mistake, Chitty learned a lot by taking the approach he did–but ultimately I don’t think it’s the most effective approach for studying nonlinear stochastic dynamical systems. It’s ironic that, around the same time Chitty’s book was published (1996), the study of population cycles made a big leap forward, thanks to the synthesis of mathematical modeling, long- and short-term data, and modern methods of time series analysis. It’s my impression that we now have a good handle on the causes of many famous population cycles, including those of many small mammals, with every prospect for further progress (see here, here, here, and here). Implicit in this recent progress, I think, is a quite different philosophy of science than Chitty’s. The book also is interesting as history. For instance, I’m told it’s more accurate than other accounts of life in Charles Elton’s Bureau of Animal Population at Oxford (where Chitty worked for over 20 years), though I can’t confirm that. Overall, it’s a very thought-provoking read, I recommend it highly, especially to students. Another review of the book here.

Let me know in the comments if you found this useful. These sorts of posts are easy for me to write, and so I’m happy to do more of them if folks want.

Book review: Experimental Evolution and the Nature of Biodiversity by Rees Kassen

Here’s something new for this blog: a timely book review. Rees Kassen‘s Experimental Evolution and the Nature of Biodiversity has just been published. Here’s my review.

Full disclosure: Rees is a friend, I spent a semester visiting his lab back in 2010. He was kind enough to send me a free copy of his book. I tried not to let it affect my review one way or the other, and I hope I managed to do that.

The book reviews what we’ve learned about evolutionary adaptation and diversification from experimental evolution of microbes. Connecting adaptation and diversification is an old problem, one Darwin himself famously struggled with. Rees is one of the world leaders in experimental microbial evolution, so his lab’s own work figures prominently in the book (without dominating it; the book is very far from just being a compilation of Rees’ own work). The chapters cover:

  • an introduction to experimental evolution (starting with a really cool example dating back to shortly after Darwin’s death)
  • the genetics of adaptation to a single environment
  • divergent selection
  • selection in spatially and temporally variable environments
  • genomics of adaptation
  • phenotypic disparity
  • rate and extent of diversification
  • adaptive radiation
  • genetics and genomics of diversification
  • the nature of biodiversity

Most of the chapters start with a stage-setting vignette to introduce and motivate interest in the topic. For instance, the chapter on adaptation to a single environment starts with the story of how Londoners sheltering in the Underground tunnels in WW II were plagued by mosquitoes that may have adapted to underground habitats, and to feeding on humans, during the 80 years the Underground had existed at that time. I really enjoyed the vignettes and found most of them effective. It’s too bad the approach kind of runs out of steam near the end of the book (there’s no vignette for the chapter on adaptive radiation, and the vignette for the following chapter was interesting but didn’t seem to me to be closely tied to the chapter topic).

Bottom line: I liked the book. Not surprisingly, perhaps, because I’m very much on Rees’ wavelength. He believes that our hypotheses should come from mathematical theory whenever possible. He thinks it’s really important to complement observational and comparative data with direct experimental tests. He believes that good data from a model system are better than no good data at all (and as his book shows, that is often a real choice we’re faced with in science). He believes that one can make useful comparisons between microcosms and other systems by keeping in mind the ways in which microcosms are different than other systems (e.g., large population sizes, adaptation based on new mutations rather than standing variation). He believes that microbial microcosms are simple enough to be tractable, but yet complex enough to be capable of surprising us, and so capable of inspiring new hypotheses as well as testing existing hypotheses. I agree on all counts.

Indeed, I wish I’d written the book myself. And I mean that almost literally, because this is kind of the evolutionary equivalent of an ecology book I proposed to write a few years ago, pulling together everything ecologists have learned from microcosm experiments. But Rees’ book is better than mine would have been, I think. One reason for that is that Rees’ book is about a fairly well-developed and unified body of theory, that’s been directly tested in a sufficient number of sufficiently-similar experiments that one can do meta-analyses on the results. I don’t know that you could say the same for my proposed book.

Those meta-analyses are the core contribution of Rees’ book, to my mind. There are about 10 meta-analyses in the book, depending on precisely how you count, many of which could’ve been standalone papers. I can only imagine how much frickin’ work it must’ve been to compile the data! If you want to know how often fitness trade-offs evolve under divergent selection (invariably), whether adaptation to a fitness peak typically involves fixation of few or many mutations (few), what the typical rate of substitution is during an adaptive walk, and much more, this book has the numbers.

The other bit of the book that really stood out for me was the extension of Fisher’s geometric model to multiple phenotypic optima, thereby converting the model into a tool for studying the consequences of divergent selection (e.g., the contrasting selection pressures imposed by two different habitats). This is a lovely idea, credited to unpublished work by G. Martin. Simple, elegant, and powerful–I can’t wait to see it further developed.

The book is a satisfying story of an ongoing, successful research program. On topics on which we have well-developed theory, microbial evolution experiments usually behave more or less as theory predicts, at least on average (there’s often a lot of variation around the average, which is something I wish Rees had discussed a bit more). The book also points out the most interesting and needed directions for future research, as a good book of this sort should do. It’ll be a gold mine for grad students looking to get up to speed on the literature and on the lookout for project ideas.

There are some weak points, though they’re far outnumbered by the strong points. There’s perhaps a bit too much repetition, with some of the same concepts and examples reintroduced in two or three places. But then, a reader who was completely new to this material might appreciate the repetition. The chapters on diversification (the second half of the book) in general weren’t quite as strong as the chapters on adaptation, probably because Rees had less material to review. So there’s less meta-analysis and more qualitative discussion of isolated examples. And I had several quibbles with the chapter on spatial and temporal variation in selection. Rees’ explanation of why geometric rather than arithmetic mean absolute fitness is of interest in temporally-varying environments isn’t as precise as I’d have liked. I wish this chapter had been clearer up front (rather than partway through) about the difference between selection that merely varies in direction in space or time, and selection that can actually stably maintain genetic variation. But I admit that’s a personal hangup of mine. I also would’ve liked to see this chapter compare spatially- or temporally-varying selection to selection in non-varying environments with the same average conditions as the varying environments, since otherwise you’re confounding the effects of environmental variance with effects of average environmental conditions. Apparently most theory or experimentation on this topic doesn’t make that comparison (unless I misunderstood something?) But that’s another personal hangup of mine. Finally, throughout the book I found myself wanting more comparison of the results of microbial evolution experiments with results from other systems. Rees’ comparative remarks often are quite brief. A few more comparative remarks might have helped to “sell” skeptical readers on the value of the experimental evolution approach. But then again, I suspect that for many topics there’s just no comparable data from other systems, and so probably there’s not much that could be said by way of comparison.

The writing is solid–simple, straightforward, and clear. The writing in several of the vignettes is really nice. In his understated way, Rees is a fine storyteller. I found myself wishing (greedily, I know) that Rees had adopted the voice of the vignettes throughout the book. The book is not at all technical, and so is quite accessible. There are hardly any equations and jargon is kept to a minimum (including genomics and sequencing jargon, thank god–I freely admit I find that stuff impenetrable). The figures are greyscale, which is sometimes ok, but sometimes you have to squint to distinguish different shades of grey. The cover art is cool, it recalls the multiple optima extension of Fisher’s geometric model that’s one of the highlights of the book.

Anyone who does experimental evolution needs a copy of this book. Who else will want to read it? In particular, why should an ecologist want to read it? I can think of a few reasons:

  • You’re broad-minded and you want to know something about how evolutionary biologists who are interested in ecology think about biodiversity. That caveat “interested in ecology” is important. Rees doesn’t take selection coefficients and population sizes as god-given. Rather, much of the book is about how the ecology of the system (and ongoing evolution) sets those parameters, thereby affecting the future course of evolution. For instance, he talks about how predators change the selection pressures to which prey are subject, while also reducing prey population sizes and so reducing the expected supply rate of beneficial mutations. And if you’re the sort of ecologist who sees genetics and genomics as far removed from anything you could possibly be interested in, well, I think you might be pleasantly surprised if you read this book.
  • You just want to understand evolution better. In particular, I think many ecologists would be surprised by, and learn a lot from, Rees’ emphasis on fitness and its evolution. For instance the idea that fitness trade-offs (i.e. high relative fitness in one environment is associated with low relative fitness in a different environment) are a result of natural selection rather than a constraint on natural selection (see this old post). And how fitness trade-offs can emerge even if the same traits are favored in all environments (just to differing degrees in different environments).
  • You’re into eco-evolutionary dynamics. Rees doesn’t use that term, and doesn’t talk a lot about coevolution (though he does talk about it a bit), but if you’re serious about the “evolution” bit of “eco-evolutionary”, you’ll want this book.
  • You buy the suggestion of Mark Vellend and others that community ecology can learn a lot from (asexual) population and evolutionary genetics. Right now, community ecologists who believe this are focusing on neutral models and elaborations thereof. I think the first community ecologist who starts translating other sorts of evolutionary genetic models into community ecology terms could (deservedly) make a splash. For instance, I bet the multiple-optima version of Fisher’s geometric model could be used to make novel predictions about community assembly and structure in spatially heterogeneous environments.

The book is softcover and it’s not expensive, so if you’re interested you should definitely buy a copy.

Book review: Community Ecology by Gary Mittelbach, and Community Ecology by Peter Morin

As a graduate student, I had the privilege of taking Peter Morin’s Community Dynamics course. In 1999, Peter published a textbook based on his course. It was very successful; as of 2011, Community Ecology is now in its second edition.

Gary Mittelbach also teaches a graduate course in community ecology. In 2012, he published a textbook based on his course, also called Community Ecology.

Originally, I had planned to review Gary’s book. Peter’s book is older, plus Peter was my Ph.D. supervisor, so I felt like reviewing Peter’s book would be some combination of not very useful and awkward. But I changed my mind, and decided it would be interesting and useful to write a joint review. The similarities and contrasts between the books provide an opportunity to talk about where community ecology is at right now and how it’s changing. And also an opportunity to talk about the difficult choices and trade-offs involved in writing a textbook (or designing a course). So this is going to be one of those book reviews where the author mostly uses the books as an excuse to talk about whatever he feels like talking about. 🙂

Let me first say that both books are very good. You can’t really go wrong with either one, I don’t think, for any purpose (you’re teaching a graduate course, you’re studying for your candidacy exam, you want a reference book…). So if all you were looking for was my opinion of both books, you can stop reading now. 🙂

They’re similar in some ways. Indeed, if you just quickly glanced at the tables of contents, you could be forgiven for thinking that the choice between the two books might as well be made with a coin flip. Here are the chapters from Peter’s book (not the actual chapter titles; just my brief summaries):

  • History of community ecology; what communities are
  • Competition theory
  • Competition data
  • Predation data
  • Predation theory
  • Food webs
  • Mutualisms and facilitation
  • Indirect effects
  • Temporal dynamics and history (phenology, priority effects and alternative states, assembly history)
  • Habitat selection
  • Spatial dynamics
  • Causes and consequences of diversity
  • Succession
  • Applied community ecology

And here are the chapters from Gary’s book (again, not the actual chapter titles, just my summaries):

  • History of community ecology; what communities are
  • Patterns of diversity
  • Biodiversity and ecosystem function
  • Population growth and density dependence
  • Basic predation theory
  • Adaptive behavior of predators and prey
  • Competition theory
  • Competition data
  • Mutualisms and facilitation
  • Food webs
  • Trophic cascades
  • Spatial dynamics
  • Metacommunities and neutral theory
  • Coexistence in variable environments
  • Evolutionary approaches (rapid evolution, eco-evolutionary dynamics, phylogenetic community ecology)
  • Open questions and future directions for community ecology

Lots of overlap there! And in some ways the topic coverage is even more similar than a glance at the tables of contents might suggest. For instance, Peter’s book covers density-dependent population growth, trophic cascades, and neutral theory, but within other chapters rather than in standalone chapters. Conversely, Gary’s book covers alternative states, but in the chapter on coexistence in fluctuating environments. The books also are similar in omitting some of the same topics. Neither has much coverage of diseases, for instance.

Both books also share a similar, powerful point of view on how to do good science, which is both explicit and implicit in both. Both books cite a wide range of different sorts of empirical work–laboratory microcosm experiments, field experiments, comparative field observations, etc. Both place a lot of emphasis on testing alternative hypotheses, and on the value of mathematical theory as a source of hypotheses, and so both books include lots of explication of theory. Gary’s book is a bit more explicit on his philosophy of theory testing (pp. 153-154). He talks about how the predictions have to follow logically from the theory’s assumptions (where have I read that before?), how to test theory, and what exactly you learn by doing so. I really liked that bit of Gary’s book.

There are differences between the books, of three interrelated sorts: organization, emphasis, and details.

One of the most important functions of a textbook is to give readers a road map to what would otherwise seem to be a trackless wilderness. As a student, it’s very difficult for you to develop your own road map of a field just by reading the primary literature and trying to figure out for yourself how the papers you’ve read are related. You can’t read enough to do it, and you’re likely to get confused by people using the same jargon to mean totally different things (“stability” is one infamous example). In contrast, Peter and Gary have spent their entire professional lives reading the literature and doing research (doing research matters here; nothing teaches you the jargon like having to use it yourself).

But the appearance of order created by any textbook is just that: an appearance. It’s an order the author imposes, not one the author discovers. Now, neither Peter or Gary imposes an idiosyncratic organization on community ecology, as evidenced by the many similarities between the two books. At some level, everyone working in a field will have similar “mental road maps” of that field. Similar, but not identical. There are some differences between Peter’s road map and Gary’s, and which one you prefer is going to be a matter of taste.

Gary’s road map is “pattern first”: he starts with large-scale patterns in biodiversity, and with the consequences of biodiversity for ecosystem function, and uses the need to explain these patterns and consequences as a motivation for subsequent discussion of processes like competition, predation, etc. Peter’s road map is “process first”: after the historical overview (which includes a cautionary note on the importance of critically evaluating hypotheses inspired by apparent patterns in one’s data*), he dives right into the processes. He then concludes the book with three chapters (the last three in my list above) on what he calls “large scale, integrative phenomena” that illustrate the joint consequences of those processes.

Obviously, either organization can work; they’re two different routes to the same endpoint. And I think the distinctions between “pattern first” and “process first” approaches are more important when it comes to doing ecology than when it comes to reading about ecology that’s already been done. There are smaller differences in organization, too. The two books group the same topics slightly differently, like two grocery stores that disagree on whether to shelve the oils with the baking goods or with the salad dressings.** But I don’t think the differences in organization are all that important.

As an aside, I’m not sure that either book is 100% successful at linking the processes that occupy most of the pages to the large-scale patterns and integrative phenomena. I think that reflects the limitations of the field of community ecology; it’s not a failing on the part of Peter or Gary. Research on large-scale patterns of biodiversity, and on biodiversity and ecosystem function, really is mostly disconnected from research on other topics in community ecology. Or, to put it in another, equivalent way so as to avoid offending anyone: research on other topics in community ecology really is mostly disconnected from research on large-scale patterns of biodiversity, and on biodiversity and ecosystem function. 🙂 We have lots of old posts discussing this disconnect with respect to large-scale patterns (here, here, here, here, here, here, and here; note that these posts are among my all-time favorites and many have great comment threads, so you should totally click through). Reflecting this disconnect, many of the topics in Gary’s first two chapters, and Peter’s last three, come off more as self-contained topics than as leading into or integrating the other material. Although Peter’s last chapter, on applied community ecology, is fairly successful as integration, I think (and while it’s a brief chapter, it’s notable because there’s no equivalent coverage of applications in Gary’s book, unless I missed it). Textbooks can’t avoid reflecting some of the limitations of the fields they cover. I do hope the next time someone writes a community ecology textbook, they’ll be able to write one that better integrates macroecology and “microecology”.

I think the biggest and most important differences between the books are in emphasis and details. As a very broad-brush generalization, I’d say that Peter’s book places more emphasis on the classics, by which I mean both classic topics, and classic studies of those topics. Gary’s book is stronger on coverage of recent “hot” topics, and places more emphasis on recent studies and the latest wrinkles. I emphasize that this is a really broad-brush generalization. Peter’s book certainly isn’t outdated in any way, and has lots of examples from the recent literature. Conversely, Gary’s book refers to many classic studies.

Obviously, there’s a trade-off between coverage of classic topics and coverage of currently “hot” topics. Trying to find the optimal point on that trade-off curve is really hard for textbook authors. It requires you to make judgement calls about what classic topics retain their interest and value. And it requires you to make judgement calls about what currently-hot topics will continue to be of interest years from now, and what currently-hot topics are just trendy bandwagons. I doubt any two ecologists would agree 100% on how to make these judgement calls (and Gary in particular writes at length about how difficult he found it to decide what topics to cover).

For what it’s worth, here are my purely personal opinions on some of the bigger differences of emphasis and detail. I like Peter’s decision to only give a couple of paragraphs and no figures to neutral theory better than Gary’s decision to devote half a chapter to it. I also like Peter’s decision to ignore phylogenetic community ecology better than Gary’s decision to devote part of a chapter to it. In making those decisions, I think Peter avoided enshrining some trendy bandwagons in his textbook. I also like Peter’s decision not to structure his whole discussion of spatial community ecology around the currently-popular metacommunity framework suggested by Leibold et al. (2004), the way Gary more or less does. On the other hand, I like Gary’s decision to talk about eco-evolutionary dynamics, which Peter doesn’t cover. And Gary’s book is much stronger than Peter’s on modern coexistence theory (a topic on which I have an old series of posts). I love that choice of Gary’s. I think that choice is going to look prescient, as modern coexistence theory becomes more widely understood and appreciated (something that’s happening already). Don’t misunderstand, Peter’s book does talk about modern coexistence theory, but does so more briefly, and more as one topic among many others. In contrast, Gary structures most of a chapter around the modern theory of coexistence in variable environments.***

Indeed, I kind of wish Gary had gone even further with his emphasis on modern coexistence theory, though if he had it would’ve been a very different sort of book. You wouldn’t realize it from Gary’s book, but modern coexistence theory isn’t just about coexistence in variable environments. It actually includes as special cases a lot of the stuff Gary talks about in other chapters–coexistence via resource partitioning, keystone predation, etc. Modern coexistence theory is about coexistence, period. I think it would be interesting for someone to write a community ecology textbook that’s structured quite differently than either Peter’s or Gary’s. One big chunk of the book (several chapters) would be on coexistence and diversity, with modern coexistence theory as the organizing principle.

In terms of other stuff, the two books are almost exactly the same length, and they’re similar in price. Gary’s book has color figures while Peter’s doesn’t, although in most cases the figures would’ve worked equally well in black and white, so I don’t think that’s a major difference.

Having trouble deciding which one to buy? Do what I did: buy both. 🙂

*Interestingly, Gary’s historical introduction includes the exact same cautionary tale: the failure of “Hutchinsonian body size ratios”, a failure which illustrates the impossibility of advancing community ecology solely with observational data and poorly-grounded hypotheses.

**What can I say, I’m a grocer’s son. 🙂

***And as part of that chapter, he says pretty much all the same things about the intermediate disturbance hypothesis that I’ve been saying on this blog (and that folks like Chesson and Huntly said in the primary literature years ago). Which made me happy. 🙂 Sadly, Gary’s book doesn’t include zombie jokes, though. 🙂