Social Science Statistics Blog

« As if winning a Nobel Prize wasn't enough... | Main | The Goal of Causal Inference »

23 January 2007

Mother Nature Estimates Using...?

So it's finally getting cold in Boston after some days that resembled Spring more than anything. Outside the buildings, smokers in T-shirts and flip-flops? The first flowers blooming?? But it's not all lost: I was just reading that an early Spring or a short interval of warm temperatures doesn't really matter for plants and animals. Plants just grow new buds or skip a year. Animals adjust their sleep patterns. But maybe Mother Nature is also smart about predicting when it's the right time to wake up. Are plants and animals Bayesians and have learned to give more weight to a signal that is a better predictor of changes in seasons than temperature?

Apparently plans and animals have an internal clock that measures the length of day and night by using length of sunlight exposure as proxy. Having been around a couple of hundred years they might know that relying on the length of day is a safer bet than relying much temperature. I wonder whether there is evidence of Mother Nature changing those weights over time, as one of the signals becomes more reliable? Maybe temperature was a better predictor when the Little Ice Age began? It wouldn't be so great to wake up when it's well below zero in late May. This would be a good example for Amy's post on Bayesian inference and natural selection (see here).

Here in the computer lab of an unnamed basement in Cambridge, MA, yours faithful won't be fooled by the temperatures either. I'll take a nap now.

Posted by Sebastian Bauhoff at January 23, 2007 12:00 PM