Books to Read While the Algae Grow in Your Fur, March 2020

Attention conservation notice: I have no taste, and no qualifications to opine about mathematical biology, the history of science, or comparative sociology and political science.

Jane Haddam, Fighting Chance

Mind candy mystery novel: the 29th, and sadly last, of her Gregor Demarkian series. This is the only one where the solution, while logical, "fair" and completely unexpected, did not feel right. (I refrain from saying any more to avoid spoilers.) It is also, as this profile notes, one where the background crime, outrageous though it sounds, was entirely real, and it's astonishing that it did not end in murder.

Nicolas Bacaër, A Short History of Mathematical Population Dynamics

This is very much a scientist's history of science, rather than a historian's. It consists of a series of very brief chapters, most of just a few pages, giving thumbnail biographies of historical figures, and explaining their contributions in modern terminology and notation. It begins with Fibonacci and his series, noting that this had absolutely no influence on any later work at using mathematics to understand population. The real development begins with stuff like life tables and actuarial calculations, Malthus and population growth, and so on. The re-appearance of the basic reproductive number in numerous contexts is a running, though not exactly high-lighted, theme. Developments in data collection (e.g., comprehensive censuses by states effective enough to actually count people, ascertain their ages, etc.) are mentioned only in passing, though without such data there would be nothing to model. The most fully developed historical study is actually one of the last, in the chapter on China's one child policy, in which a bunch of control engineers, cut off from the broader scientific community, manage to re-invent key ideas of demography, derive radical conclusions from their models, and get men in power to act on them.

I learned from this, I appreciate its perspective and its brevity, and I'd assign it to my students if they were curious, but I'd also like to see something more historically serious.

Meg Gardiner, UNSUB, Into the Black Nowhere, The Dark Corners of the Night

Mind-candy thrillers, psycho-killers-and-profilers flavored. Competitive with Shadow Unit as high-quality Criminal Minds pastisches.

Brian D. Ripley, Spatial Statistics

On the one hand, this is from 1981, so all the detailed computational advice is laughably obsolete. (At one point, Ripley discusses strategies for not having to keep all of a 128 kb image in main memory at once.) There has also been a lot of advances in some aspects of the theory, notably point processes. On the other hand, Ripley's basic advice --- visualize; do less testing for "randomness" and more model-building; simulate your models, visualize the simulations, and test modeling assumptions with simulations and visualizations; smooth, and remember that "kriging" is just the Wiener filter --- remains eminently sound.

--- I have been reading bits and pieces of this book, off and on, since around 2000, but I have a rule about not recommending something until I've finished it completely. Having finally now read it all, including the chapter on tomography (!), I can safely say: anyone seriously interested in spatial statistics probably ought to read this, but you can skip the tomography chapter as obsolete. I have to say that the idea of paying the list price for the paperback is outrageous, but lots of potential readers will have access to Wiley's online version, which is a perfectly decent scan of the printed book.

Victor LaValle, The Changeling

Magical-realist urban fantasy, about being a parent in contemporary New York. It's intense, but it's great because it honors the genre conventions of both literary fiction (the attention to character;