Twitter science

Discussing science on the internet can be interesting at times, even on Twitter, which seems to have been designed specifically to foster misunderstanding by way of brevity. Here are two examples from my week.

Early in the week, Brian Brettschneider, a climatologist in Alaska, put up a global map of monthly precipitation variability:
Brettschneider map
Brian said the metric graphed constitutes the percentiles of a chi-square goodness-of-fit test comparing average monthly precipitation (P) against uniform monthly P. I then made the point that he might consider using the Poisson distribution of monthly P as the reference departure point instead, as this was the more correct expectation of the “no variation” situation. Brian responded that there was no knowledge, or expectation, regarding the dispersion of data, upon which to base such a decision. That response made me think a bit, and I then realized that I was thinking of the issue in terms of variation in whatever driving processes lead to precipitation measured at monthly scales, whereas Brian was thinking strictly in terms of the observations themselves–the data as they are, without assumptions. So, my suggestion was only “correct” if one is thinking about the issue the way I was. Then, yes, the Poisson distribution around the overall monthly mean, will describe the expected variation of a homogeneous, random process, sampled monthly. But Brian was right in that there is no necessary reason to assume, apriori, that this is in fact the process that generated the data in various locations.

The second interchange was more significant, and worrisome. Green Party candidate for President, physician Jill Stein, stated “12.3M Americans could lose their homes due to a sea level rise of 9ft by 2050. 100% renewable energy by 2030 isn’t a choice, it’s a must.” This was followed by criticisms, but not just by the expected group but also by some scientists and activists who are concerned about climate change. One of them, an academic paleoecologist, Jacquelyn Gill, stated “I’m a climate scientist and this exceeds even extreme estimates“, and later “This is NOT correct by even the most extreme estimates“. She later added some ad-hominem barbs such as “That wasn’t a scientist speaking, it was a lawyer” and “The point of Stein’s tweet was to court green voters with a cherry-picked figure“. And some other things that aren’t worth repeating really.

OK so what’s the problem here? Shouldn’t we be criticizing exaggerations of science claims when they appear in the mass culture? Sure, fine, to the extent that you are aware of them and have the time and expertise to do so. But that ain’t not really the point here, which is instead something different and more problematic IMO. Bit of a worm can in fact.

Steve Bloom has been following the climate change debate for (at least) several years, and works as hard to keep up on the science as any non-scientist I’ve seen. He saw Gill’s tweets and responded, that no, Stein’s statement did not really go so far beyond the extreme scientific estimates. He did not reference some poor or obsolete study by unknown authors from 25 years ago, but rather a long, wide ranging study by James Hansen and others, only a few months old, one that went through an impressive and unique open review process (Peter Thorne was one of the reviewers, and critical of several major aspects of the paper, final review here, and summary of overall review experience here). Their work does indeed place such a high rate of rise within the realm of defensible consideration, depending on glacier and ice sheet dynamics in Greenland and Antarctica, for which they incorporate into their modeling some recent findings on the issue. So, Jill Stein is not so off-the-wall in her comments after all, though she may have exaggerated slightly, and I don’t know where she got the “12.3M homes” figure.

The point is not that James Hansen is the infallible king of climate science, and therefore to be assumed correct. Hanson et al. might be right or they might be wrong, I don’t know. [If they’re right we’re in big trouble]. I wasn’t aware of the study until Steve’s tweeted link, and without question it will take some serious time and work to work through the thing, even just to understand what they claim and how they got there, which is all I can expect to achieve. If I get to it at all that is.

One point is that some weird process has developed, where all of a sudden a number of scientists sort of gang up on some politician or whatever who supposedly said some outrageous thing or other. It’s not scientist A criticizing public person B this week and then scientist C criticizing public person D the next week–it’s a rather predictable group all ganging up on one source, at once. To say the least, this is suspicious behavior, especially given the magnitude of the problems I see within science itself. I do wonder how much of this is driven by climate change “skeptics” complaining about the lack of criticisms of extreme statements in the past.

To me, the bigger problem is that these criticisms are rarely aimed at scientists, but rather at various public persons. Those people are not immune to criticism, far from it. But in many cases, and clearly in this one, things being claimed originate from scientists themselves, in publications, interviews or speeches. For the most part, people don’t just fabricate claims, they derive them from science sources (or what they consider to be such), though they certainly may exaggerate them. If you don’t think the idea of such a rapid rise is tenable, fine…then take Hanson et al. to the cleaners, not Jill Stein. But, unless you are intimately familiar with the several issues involving sea level rise rates, especially ice melt, then you’ve got some very long and serious work ahead of you before you’re in any position to do so. This stuff is not easy or simple and the authors are no beginners or lightweights.

The second issue involves the whole topic of consensus, which is a very weird phenomenon among certain climate scientists (not all, by any means). As expected, when I noted that Stein was indeed basically referencing Hanson et al., I was hit with the basic argument (paraphrased) “well they’re outside of the consensus (and/or IPCC) position, so the point remains”. Okay, aside from the issues of just exactly how this sacred consensus is to be defined anyway… yeah, let’s say they are outside of it, so what? The “consensus position” now takes authority over evidence and reasoning, modeling and statistics, newly acquired data etc., that is, over the set of tools we have for deciding which, of a various set of claims, is most likely correct? Good luck advancing science with that approach, and especially in cases where questionable or outright wrong studies have formed at least part of the basis of your consensus. It’s remarkably similar to Bayesian philosophy–they’re going to force the results from prior studies to be admitted as evidence, like it or not, independent of any assessment of their relative worth. Scientific ghoulash.

And yes, such cases do indeed exist, even now–I work on a couple of them in ecology, and the whole endeavor of trying to clarify issues and correct bad work can be utterly maddening when you have to deal with that basic mindset.

Well, how ’bout that

The blog known as “RealClimate” has put up a couple of posts on its first ten years this week, here and here. Surprisingly, they state that they’ve “done well” and honor themselves for their ability to do what others couldn’t or wouldn’t 10 yrs back. Well, this is good stuff indeed.

In the interest of public education I’ll be providing a little additional insight when time and energy allow. Just a little, say 4/10 = 40% or so maybe.

Liberian ebola rate jumps

Updated as of 09-18-2014 WHO report.

Many reports from on-the-ground workers with the WHO, Doctors Without Borders, state health and aid agencies, etc. have commented that the case and death rates in at least some locations have almost certainly been too low, because of a substantial number of people avoiding going to clinics and hospitals, out of fear primarily. This situation seems to be the worst in Liberia. See this article for example. Today’s WHO-released data from Liberia may be confirmation of this, many new cases and deaths being reported there from August 16-18. Such an explanation could be due to more intensive case tracking/finding. However, it is also possible that the epidemic is simply exploding there now, especially given that it is well established in the capitol of Monrovia. Or it could be due to some combination of the two.

In the graphs below I used a pretty stiff “span” parameter (span = 1.0) in the loess smoothings (dark black lines) of the WHO-reported raw data (thin line). This choice gives about 35 deaths/day in Liberia. If I use something more flexible, span = 0.5 for example, the estimated rates are higher, about 47/day. However, it’s best to go stiff (i.e. conservative) here, because clearly there are major variations due to data gathering and reporting timelines that have been causing large fluctuations in the numbers (discussed more here).  But there’s also clearly more than just that going on with this latest surge in numbers.

This situation is now extremely serious, if it wasn’t already. Note also that negative rates early on in the outbreak are presumably due to case retractions or re-classifications. Code generating data and graphs is here and data table itself is here.

Continue reading

Recent advancements on the “consensus” science front

Real good news from the world of science, just last week. Science as we all know, is all about “pushing the envelope”, about stretching the frontiers of knowledge, about intrepid explorations right on that knife-edged ridge that typically divides brilliance from ignorance and ineptitude. Science–let’s cut to the chase here–is all about putting it all out there on the line, in the quest for deep truths that affect us all.

Just last week, Climatic Change pushed on that envelope big time, with a fabulous discovery. A team of four researchers have discovered that, in situations where you’re having trouble getting people to buy in on a supposed “consensus” on some topic, such as say the 97 percent consensus regarding human effects on climate change, what you want to do there is to use either “simple text” or a “pie chart”. For the unfamiliar, pie charts are round, graphical devices in which a portion, p, of the round image is shaded one color and the remaining portion, 1-p, is shaded a different color altogether. [For sake of simplicity I have limited our hypothetical chart to two colors; advanced pie charts will sometimes use more than two colors, but we can simplify here without loss of generality]. “Simple text” is just what it says, sometimes even simpler.

When the human eye/brain/sensory system views said chart, an impression in the mind is created in which the two (or more) color shadings approximate actual fractional values of 1.0. Some refer to this as the theoretical/neurological basis of the pie chart. [Others do not; there is no consensus on that issue]. The point is, the pie chart can approximate an actual number!** This makes all the difference when trying to get a point across to the random ignoramus on the street.

I should caution the amateur scientists out there to please not try this at home. This type of research involves heavy duty online questioning* following, strict survey science guidelines, as informed by “metaphor meta-reviews for optimal persuasiveness”. It can involve the random insertion of questions involving “Angelina Jolie’s double mastectomy” so as not to divulge one’s true intentions. Not divulging one’s true intentions is a highly refined skill in consensus science–not just anybody can do it. This stuff takes training.

Well we’re out of time now but we can probably expect many future breakthroughs in the exciting world of “consensus” science studies as they relate to climate, and hopefully can investigate these as they occur, should we have the necessary chops and patience.

* The authors note: “All treatments contained the following message; ‘97% of climate scientists have concluded that human-caused climate change is happening’. To enhance the credibility of the treatment, the logo of the American Association for the Advancement of Science (AAAS) was visible on every message.”. Not that the credibility of the “treatment” needs enhancing mind you, nor that AAAS partially funding the study has any relevance here; let’s not jump to any conclusions.

** This process can be enhanced by what professional pie chart communicators term “overlaying” the actual numerical number right on the pie chart itself, viz:
vanderlinden etal SM figure 2

Phenotypic plasticity and climate adaptation; ecology vs natural history

For those interested in the potentially very important issue of biological adaptation to climate change, you will definitely want to check out the latest issue of Evolutionary Applications, a special issue addressing climate change, adaptation and phenotypic plasticity, all articles open. I’ve not yet been able to read any of the articles, but it looks really good from first glance and I’m certain I will learn a lot from it.

That second phrase there is the topic of Jeremy Fox’s latest post at Dynamic Ecology, and he’s outdone even himself this time; go see, once again, how good blog articles and their discussions can be when the effort is made. I wish I had time to respond to it with anything more than the couple of sentences I stated there, but I do not–whatever extra time I have is devoted to just reading (including the comments) and thinking about it. And those discussions over there give you a lot to think about.