We are not making this up. That's the subject of animal behaviorist R.A. Hinde's 1951 PhD Thesis, published by Oxford University. Of course, he's referring to the birds, Parus major, which are the biggest tits in the world, and are known under the common name Great Tit. American tits, Parus bicolor, are much smaller, like the European blue tit, Parus caeruleus.

And it's those tits the journal Science is saying global warming may affect.

Is this the same old story, which typically assumes that some organism, (in this case, tits) aren't up to adapting their behavior to rapidly changing temperatures? One problem for nesting birds, for example, is timing their reproduction to match the availability of food. With all those voracious little mouths to feed, there had better be an adequate food supply each year.

Turns out, it's not the same ole same old. It looks like tits will be OK in a warmer world. Dutch ecologist Fabrizio Grieco and two colleagues carefully monitored blue tit pairs over the course of two consecutive years. In the first year, half of the tit pairs were supplied with a robust diet of caterpillars and mealworms to feed their hatchlings, while the other half, the control group, were left hanging. These resulting hungrier control birds had a tendency to breed later in the first year. But in the following year, they bred much earlier as a precaution to take advantage of the peak in caterpillar abundance that matches the leafing out of young foliage. By contrast, the plump, well-fed tits, apparently assuming the good times would continue, actually tended to breed later in the second year. In both cases, the blue tits took their breeding cues from conditions in the previous year.

It's interesting that blue tits have among the shortest life spans of all birds. About half of the population dies each year. The observation that these short-lived species can adapt their behavior so quickly to environmental cues suggest that most other birds, which live much longer, will have even less difficulty. This study casts doubt on earlier climate change impact studies suggesting that warming will significantly throw off the timing of biological events (like leaf and caterpillar emergence and bird breeding) resulting in devastating ecological consequences.

To the contrary, it appears that if British blue tits can flourish in a warmer world, then tits worldwide are sure to thrive.

Reference:

Grieco, F., A.J. van Noordwijk, and M.E. Visser, 2002. Evidence of the effect of learning on timing of reproduction in blue tits, Science, 296, 136–138.

How Not To Use GCM Output

Let's say, hypothetically, that you live in Slovenia. Furthermore, let's say you've always been interested in the flowering dates of dandelions. Finally, as a nature lover, you're naturally concerned about how global warming might influence the flowering dates of dandelions in the year 2049. What tools might you employ?

The answer, of course, is General Circulation Models (GCMs). Yes, the same GCMs that can't reproduce past or current climate can help predict future dandelion flowering dates in Slovenia. So claim scientists from Slovenia's Center of Agrometeorology in a recent paper in the International Journal of Biometeorology.

Of course, we at WCR have a long history of keeping tabs on the misuse of GCM output. In one respect, nearly any use of GCM output other than model validation could be considered misuse. Even the modelers themselves consistently contend that their output is not valid at the regional or subregional scale.

Yet GCModelers do not hesitate to provide future climate projections for any individual grid box for anyone who asks. The computers produce the output, so why not use it? It's disappointing how many of these papers on the impacts of local or regional climate change make it into the hallowed refereed scientific literature.

One of the hot topics in climate change today is "downscaling," a statistical procedure whereby the researcher takes useless GCM projections for a large region and, through a series of complex mathematical and statistical analyses, converts them to useless GCM projections for a much smaller region.

And that brings us back to Slovenia. In what has to be the most extreme example of downscaling we've seen thus far, the Slovenian team takes data from the GCM scale (Eurasia?) and downscales the data to the level of the dandelion. That feat obviously requires quite a lot of work—enough to fill 11 journal pages with complex equations, tables, and graphics. And the result? (We hope you're sitting down for this shocker...) In comparison to the period 1960–1989, dandelions in 2020–2049 will flower about 10 days earlier. That's right—warmer weather promotes earlier flowering!

There of course are other ways to arrive at that prediction that don't require GCMs. For example, you could compare flowering times in warm years vs. cold years to try to establish the underlying relationship. You could then use that observed relationship (which is based on real weather and real plant observations) to predict flowering dates for data that were withheld from the original analysis. That kind of approach has been used successfully for more than a century. Of course, it has the "disadvantages" of being simple and not requiring the use of costly and suspect GCM output and the application of that output at a spatial scale for which it was not intended. What's worse, its utter simplicity might discourage journal editors from publishing it. A final disadvantage is that some GCMs predict warming of a magnitude that has not been observed in recent history, so the results that don't require GCM output are far less dramatic and potentially less devastating to the environment.

As computing speed continues to increase, GCMs will continue producing output at finer and finer spatial resolution. As that happens, downscaling will lose favor. But because of the lack of inherent predictability in the earth's climate system, the results will be no more valid at that scale than they are today at more coarse resolutions. At that point, perhaps even nuclear physicists will gain entré into the world of climate change funding by examining the impact of global warming on the subatomic level, as guided by GCM output.

Reference:

Bergant, K., J. Kajfez-Bogataj, and Z. Crepinsek, 2002. Statistical downscaling of general circulation model–simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia, International Journal of Biometeorology, 46, 22–32.