This talk is going to be harder to summarize without the visuals used during the presentation. I’m googling to see if I can find an online copy of some of the graphs and maps that Dr. Hamilton used to illustrate her work – it looks like they are not immediately available. But in summary, GYC and Dr. Hamilton have partnered to look in detail at the GYE to try to develop some idea of what is actually going on with climate, based on weather station data from the past century. Using USDA information on temperature and precipitation, they’ve constructed a historical timeline of average temperature and precipitation from 1900-1970, and then looked at places where, over the past thirty years, temperature or precipitation have varied by more than two standard deviations from the 1900-1970 averages. For people without a background in statistics, two standard deviations from average is significant because about 98% of variation in any situation should fall within the boundaries of two standard deviations from whatever the average of the data is. So if you see something that is more than two standard deviations from the average, you can be pretty sure that something out of the ordinary is occurring.
The standard narrative of climate change around the world is that temperature is rising, which is true, but how this plays out a local scale can be extremely varied. This is why there’s still so much room to sow doubt and confusion over the climate science.
Dr. Hamilton’s data suggest that average minimum temperatures are increasing, particularly in late winter and early spring, but that average maximum temperatures are not increasing. This means that, as Dr. Hamilton puts it, “we are losing climate space” on the colder end of the spectrum, but not necessarily gaining it on the warmer end. Precipitation seems to be decreasing in July, but by October it’s increasing; by December, it’s leveled out and remains approximately the same as it has been since 1900. A few places seemed resistant to the general loss of minimum temperatures, among them the northwestern edge of the Wind River Range.
So what does all of this mean for the future of the ecosystem? Difficult to say for sure, but this is certainly the next step in the climate change narrative – boring down into local trends and trying to create scenarios that will allow planning for adaptation.
Three things in the presentation were particularly striking. The first was Dr. Hamilton’s opening statement, in which she briefly addressed the politics of climate change and then said she didn’t want to talk about it. Who does? I sympathize with her. But whether we want to talk about it or not, the gridlock over climate change policy is the problem with which we really need to be wrestling. Falling back on science and scientific management, generating more data and more maps, isn’t going to convince people who already believe that researchers like Dr. Hamilton are being paid off to do the work they do. (They aren’t. Just because the right wing pays its ‘scientists’ to generate data doesn’t mean that real researchers lack integrity.)
The second was the predominance of maps in the presentation. Some colleagues of mine have an old joke that asserts that when environmentalists are in doubt about what to do, they fall back on producing maps. Sure enough, in the face of climate change policy gridlock, we are indeed producing more maps. The maps are beautiful, fascinating, informative, and represent great research. Hopefully they will make an important contribution to conservation planning in the GYE. But maps aren’t solutions, and to put these maps to good use, we need something more.
The third thing, which I found hopeful and which partially addresses the concern above, was the suggestion that the GYE would be the test case for how to use tools like these maps, because the region has such a broad conservation constituency. Let’s hope that the support for conservation values does translate to some form of planning for ecosystem resilience at a broad scale. But the challenges are still manifold, and those problems aren’t scientific problems – they’re people problems, and they’re governance problems.