Birdy statistics

I’m not sure about this fascinating article on birds evolving to avoid cars in the US.

The story is that fewer cliff swallows are being killed on the roads AND those birds killed have longer than average wings. The argument here is that longer wings make for less agility, making the birds more likely to be killed by cars.

So far so good. But then:

The authors of the study found that over a 30 year period, annual cliff swallow roadkill has declined steadily from 20 birds per season in 1984 and 1985 to less than five birds per season during the last five years. Over the same period, traffic volumes remained the constant and the overall bird populations increased.

I am not an ornithologist or evolutionary expert, but I just can’t see how between 20 and 5 birds killed per season will create enough selection pressure to change the wingspan.

The original research summary is far more persuasive than the article. It shows graphs and statistical test results for decreasing average population wing size and increasing average road-kill wing size over time.

The explanation of why the average wingspan for cliff swallows killed be vehicles should increase is left unexplained. It does rather suggest potential measurement or confirmation bias from the research team – once the hypothesis starts looking interesting it would be very easy to unintentionally bias the measurements.  Measuring wingspan accurately to within a few millimetres is fraught with risks of subjective error.

Further, it looks like around 3 data points contribute significantly to the low p values of the tests and I would be very curious to know how robust the results were to removal of these influential points. It looks like the trends might remain, but without anything close to the significant suggested by the original research.

Finally, the clustering of wing measurement points in certain years suggests different levels of care and accuracy in measurement and potential “anchoring and adjustment bias”. It’s very hard to apply the same measurement protocols over 30 years.

So, fascinating research, interesting conclusion, but I’m left somehow unconvinced. It’s a pity the statistics applied weren’t a little more robust and the obvious criticisms weren’t addressed.