No, those two aren't actually related, except for the fact that it's plug day here at Nathan Explains Science.
"The New School of Fish" in San Francisco Magazine
First, I want to draw your attention to this story on how hard it is to find out where your salmon is coming from, despite the fact that restaurants practically get you the name of the cow you're eating. Erik Vance, the author, and I are member's of the Science Writer's Posse, a science freelancers' group, and this has been a long labor of love for him. You'll learn some cool (if distressing) stuff reading it.
I feel I should point out my (science) colleague Jen Dunne, an ecologist who is collaborating on the first (!) study of human impact on food webs, or, put another way, actually treating people like they're part of the ecosystem and have an impact on it, just like every other living thing.
Also, I should tell you that this is something of a personal issue for me, because fish and salmon in particular are a big part of the Pacific Northwest culture I grew up in. Farmed salmon, while they seem like a good idea, are susceptible to parasites that can eventually get out into the wild population, and that's just one of the problems. Here's a Seattle PI blog post from a couple years ago where you can learn more—but don't forget to check out Erik's story!
At Long Last, A Behavioral Model of Elections Gets Published
Okay, that may be an exaggeration, but here's the deal. Political scientists and economists of the mathematical theory persuasion usually make rather strong and typically silly assumptions about how voters and politicians alike make decisions. For example, theorists generally model politicians as if they actually knew how voters' beliefs about policy are distributed in the population.
Realizing (some time ago) that this was silly, some political scientists started looking at adaptive models. This, in fact, is my area of research, and I've worked on adaptive models of voter turnout. The idea is that rather than having access to tons of information and, for example, voting for the very best politician for you, you (not so much you the reader as the average person) make a decision, get some feedback, and adjust your thinking and decisions next time around. The key idea is that you get information spread out over time rather than up front and all at once, and as you gather information, you adapt.
I suspect that many academics avoid this stuff because it's not mathematically simple—in fact, you often have to rely on computer simulation techniques to get the models to predict anything—but that shouldn't stand in the way of more realistic theories.
Thus, to those of us in the field at least, a new book by my close colleagues Jon Bendor (my advisor), Daniel Diermeier, Dave Siegel, and Mike Ting that combines mathematical and computer modeling to study, for example, how politicians' stands change over time, is a major step forward. The book, A Behavioral Model of Elections, has been a long time coming, but contains some of the best theoretical work yet done on how elections work. It's surprisingly inexpensive and promises to be a great read. Check it out.