Tag Archives: global warming

On Global State Shifts

This is a edited version of a post I sent out to the E-ANTH listserv in response to a debate over a recent paper in Nature and the response to it on the website “Clear Science,” written by Todd Meyers. In this debate, it was suggested that the Barnosky paper is the latest iteration of alarmist environmental narratives in the tradition of the master of that genre, Paul Ehrlich. Piqued by this conversation, I read the Barnosky paper and passed along my reading of it.

The Myers’s piece on the “Clear Science” web site is quite rhetorically clever. Climate-change deniers have a difficult task if they want to convincingly buck the overwhelming majority of reputable scientists on this issue. Myers uses ideas about the progress of science developed by the philosopher Thomas Kuhn in his classic book, The Structure of Scientific Revolutions. By framing the Barnosky et al. as mindlessly toeing the Kuhnian normal-science line, he has come up with a shrewd strategy for dealing with the serious scientific consensus around global climate change. Myers suggests that “Like scientists blindly devoted to a failed paradigm, the Nature piece simply tries to force new data to fit a flawed concept.”

I think that a pretty strong argument can be made that the perspective represented in the Barnosky et al. paper is actually paradigm-breaking. For 200 years the reigning paradigm in the historical sciences has been uniformitarianism. Hutton’s notion — that processes that we observe today have always been working — greatly extended the age of the Earth and allowed Lyell and Darwin to make their remarkable contributions to human understanding. This same principle allows us to make sense of the archaeological record and of ethnographic experience. It is a very useful foil for all manner of exceptionalist explanatory logic and I use it frequently.

However, there are plenty of ways that uniformitarianism fails. If we wanted to follow the Kuhnian narrative, we might say that evidence has mounted that leads to increased contradictions arising from the uniformitarian explanatory paradigm. Rates of change show heterogeneities and when we trying to understand connected systems characterized by extensive feedback, our intuitions based on gradual change can fail, sometimes spectacularly. This is actually a pretty revolutionary idea, apocalyptic popular writings aside, in mainstream science.

Barnosky et al. draw heavily on contemporary work in complex systems. The theoretical paper (Scheffer et al. 2009) upon which the Barnosky paper relies heavily represents a real step forward in the theoretical sophistication of this corpus and does so by making unique and testable predictions about systems approaching critical transitions. I have written about it previously here.

The most difficult part of projecting the future state of complex systems is that human element. This leads too many physical and biological scientists to simply ignore social and behavioral inputs. This said, there are far too few social and behavioral scientists willing to step up and do the hard collaborative work necessary to make progress on this extremely difficult problem. The difficulty of projecting human behavior often leads to projections of the business-as-usual variety and, unfortunately, these are often mischaracterized by the media and other readers. Such projections simply assume no change in behavior and look at the consequences some time down the line. A business-as-usual projection actually provides a lot of information, albeit about a very hypothetical future. What if things stayed the way they are? Yes, behavior changes. People adapt. Agricultural production becomes more efficient. Prices increase, reducing demand and allowing sustainable substitutes. Of course, sometimes things get worse too. Despite tremendous global awareness and lots of calls to reduce greenhouse gas emissions, carbon emissions have continued to rise. So, there is nothing inherently flawed about a business-as-usual projection. We just need to be clear about what it means when we use one.

A criticism that emerged on the list is that Barnosky et al. is essentially “an opinion piece.” However, the great majority of the Barnosky et al. paper is, in fact, simply a review. There are numerous facts to be reviewed: biodiversity has declined, fisheries have crashed, massive amounts of forest have been converted and degraded, the atmosphere has warmed. They are facts. And they are facts in which many vested interests would like to sow artificial uncertainty for political purposes. Positive things have happened too (e.g., malaria eradication in temperate climes, increased food security in some places that used to be highly insecure, increased agricultural productivity — though this may be of dubious sustainability), though these are generally on more local scales and, in some cases, may simply reflect exporting the problems to rich countries to the Global South. The fact that they are not reviewed does not mean that the paper belongs in an hysterical chicken-little genre.

A common critique of the doomsday genre is the certainty with which the horrible outcomes are framed. The Barnosky paper is suffused with uncertainty. In fact, this is the main point I take away from it! The first conclusion of the paper is that “it is essential to improve biological forecasting by anticipating critical transitions that can emerge on a planetary scale and understanding how such global forcings cause local changes.” This suggests to me that the authors are acknowledging massive uncertainty about the future, not saying that we are doomed with certainty. Or how about: “the plausibility of a future planetary state shift seems high, even though considerable uncertainty remains about whether it is inevitable and, if so, how far in the future it may be”?

Myers writes “they base their conclusions on the simplest linear mathematical estimate that assumes nothing will change except population over the next 40 years. They then draw a straight line, literally, from today to the environmental tipping point.” This is a profoundly misleading statement. Barnosky et al. are using the fold catastrophe model discussed in Scheffer et al. (2009). The Scheffer et al. analysis of the fold catastrophe model uses some fairly sophisticated ideas from complex systems theory, but the ideas are relatively simple. The straight line that so offends Myers arises because this is the direction of the basin of attraction. In the figure below, I show the fold-catastrophe model. The abcissa represents the forcing conditions of the system (e.g., population size or greenhouse gas emissions). The ordinate represents the state of the system (e.g., land cover or one of many ecosystem services). The sideways N represents an attractor — a more general notion of an equilibrium. The state of the system tends toward this curve whenever it is perturbed away.

The region in the interior of the fold (indicated by the dashed line) is unstable while the upper and lower tails (indicated by solid lines) are stable and tend to draw perturbations from the attractor toward them. The grey arrows indicate the basin of attraction. When the system is perturbed off of the attractor by some random shock, the state tends to move in the direction indicated by the arrow. When the state is forced all the way down the top arc of the fold, it enters a region where a relatively small shock can send the state into a qualitatively different regime of rapid degradation. This is illustrated by the black arrow (a shock) pushing the state away from point F2. The state will settle again on the attractor, but a second shock will send the state rapidly down toward the bottom arm of the fold (point F1). Note that this region of the attractor is stable so it would take a lot of work to get it back up again (e.g., reduce population or drastically reduced total greenhouse gasses). This is what people mean when they colloquially refer to a “global tipping point.”

This is the model. It may not be right, but thanks to Scheffer et al. (2009), it makes testable predictions. By framing global change in terms of this model, Barnosky et al. are making a case for empirical investigation of the types of data that can falsify the model. Maybe because of the restrictions placed on them by Nature (and these are severe!), maybe because of some poor choices of their own, they include an insufficiently explained, fundamentally complex figure that a critic with clear interests in muddying the scientific consensus can sieze on to dismiss the whole paper as just more Ehrlich-style hysteria.

For me — as I suspect for the authors of the Barnosky et al. paper — massive, structural uncertainty about the state of our planet, coupled with a number of increasingly well-supported models of the behavior or nonlinear systems (i.e., not simply normal science) strongly suggests a precautionary principle. This is something that the economist Marty Weitzman suggested in his (highly technical and therefore not widely read) paper in 2009 and that I have written about before here and here. This is not inflammatory fear-mongering, nor is it grubbing for grant money (I wish it were that easy!). It is responsible scientists doing their best to communicate the state of the science within the constraints of society and the primary mode of scientific communication. Let’s not be taken in by writers pretending to present “just the facts” in a cool, detached manner but who actually have every reason to try to foment unnecessary uncertainty about the state of our world and impugn the integrity of people doing their level best to understand a rapidly changing planet.

References

Kuhn, T. 1962. The Structure of Scientific Revolutions. Chicago: University of Chicago Press.

Scheffer, M., J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk, and G. Sugihara. 2009. Early-Warning Signals for Critical Transitions. Nature. 461 (7260):53-59.

Weitzman, M. L. 2009. On Modeling and Interpreting the Economics of Catastrophic Climate Change. The Review of Economics and Statistics. XCI (1):1-19.

 

Jennifer Burney Lecture

I’ve spent the better part of the day editing web pages as I prepare to teach two courses this spring. Given that I’ve more-or-less wasted the day with necessary but not especially intellectually rewarding tasks, I thought that I would take a moment to post something really important and scientifically interesting. Jennifer Burney, of Stanford’s Program in Food Security and the Environment, gave a talk entitled “Food’s Footprint: Agriculture and Climate Change” at Oregon State‘s Food for Thought Series. We’ve known Jen for a long time now.  If memory serves me correctly, she was in my wife Libra‘s section of the American Civil War at Harvard in Fall of 1995. Later she was a student in Mather House, where we were resident tutors from 1997-2001. She went on to do a Ph.D. in physics at Stanford and then moved into a post-doctoral fellowship at FSE.

Jen and all the folks at FSE are doing great and fundamental work.  In this talk, she presents results that may seem somewhat counter-intuitive. Namely, she shows that the agricultural intensification attendant to the Green Revolution has been good for global carbon budgets — and feeding hungry people.  It’s all about counterfactuals. I am looking forward to reading this work since some of these counterfactuals depend critically on demographic assumptions.

As she says in the talk, just because the results suggest that intensive agriculture is good from a global warming perspective, doesn’t take Big Agriculture off the hook. There are items that their models don’t incorporate (but could in principle) and they don’t consider anything other than carbon budgets.  It would be nice to think of a way of uniting all the costs and benefits of intensification in a single framework.

This is very important stuff and the work highlights the complexities of population, environment, and food production. I look forward to seeing more work from Jen and her collaborators at FSE.

Stanford Migration and Adaptation Workshop

Information on our NICHD-funded April formal demography workshop on migration and adaptation is now posted on the website Stanford Center for Population Research (SCPR, pronounced “scooper”).  SCPR is itself hosted by Stanford’s Institute for Research in the Social Sciences (IRiSS), which is also the umbrella organization for the Methods of Analysis Program in the Social Sciences (MAPSS), a program that I currently direct. We will be having this little shindig at the new IRiSS facility on Alta Road, a lovely location on the hill behind Stanford’s main campus, quite near the Center for Advanced Study in the Behavioral Sciences. All of these workshops have been terrific, but I am particularly excited about this one because it brings together so many of the threads of work going on right here at Stanford on human ecology, demography, and the biophysical environment.  Much of this work is facilitated by the Woods Institute for the Environment, where I and a number of the other Stanford-based speakers sit.

As a quick teaser of the kind of work that we will discuss, I want to draw people’s attention to two papers by Stanford faculty participating in the workshop that are just out this week.  Eric Lambin has a paper (which also happens to be his inaugural paper in PNAS as a member of the NAS) on the interactions between globalization, land use, and future land scarcity. I saw a talk on this last week and it was terrific. Lambin and co-author Patrick Meyfroidt argue that there are four socio-economic mechanisms (displacement, rebound, cascade, and remittance effects) that are amplified by by the process of economic globalization and that can accelerate land conversion. David Lobell has a new paper out today in Nature Climate Change in which he and his co-authors capitalize on a treasure-trove of historical agricultural trials in Africa to measure the impact of warming on maize production.  They find that approximately 65% of areas will experience a decline in productivity with a one-degree rise in global temperature if rain patterns are optimal.  If rain is sub-optimal, as is likely to be the case, then every site would experience reduced productivity.  This supports David’s contention that the effects on agricultural productivity of temperature increase from global climate change can not be understood except in the context of changes in rainfall as well.

Potential students who are interested in studying these issues at Stanford have a number of options.  If anthropology is your thing, we have a Ph.D. focus area in Ecology and Environment within the Department of Anthropology.  Bill Durham, Lisa Curran, Rebecca Bird, Douglas Bird, and I all teach in this area. Another option, for the more interdisciplinarily inclined, is E-IPER.  This is a topic I will have to take up in more detail in a later post since I actually have to do some work organizing our workshop now!

Winter Weirding

As I listen to the deluge of reports of horrible winter weather from friends back on the east coast, I came across this video by Peter Sinclair from his YouTube series, “Climate Denial Crock of the Week.” The part I find most compelling is the animation toward the end of this short video showing what looks an awful lot like the displacement of cold Arctic air down into North America and Eurasia by much warmer (as high as 20 degrees F) in the Arctic.

Worrying Trends

The UN’s Food and Agriculture Organization‘s food price index is at an all-time high, meaning that the food security of millions of people is in jeopardy. In the plot below (click to enlarge), we can see that the FPI currently just exceeds its previous high in June of 2008, when riots over food shortages were widespread. This is something to keep an eye on for the new year.

fpi-ts-1990-2010

Fold Catastrophe Model

My last post, which I had to cut short, discussed the recent paper by Scheffer et al. (2009) on the early warning signs of impending catastrophe. This paper encapsulates a number of things that I think are very important and relate to some current research (and teaching interests). Scheffer and colleagues show the consequences on time series of state observations when a dynamical system characterized by a fold bifurcation is forced across its attractor where parts of this attractor are stable and others are unstable.  In my last post, I described the fold catastrophe model as an attractor that looks like an “sideways N.” I just wanted to briefly unpack that statement.  First, an attractor is kind of like an equilibrium.  It’s a set of points to which a dynamical system evolves.  When the system is perturbed, it tends to return to an attractor.  Attractors can be fixed points or cycles or extremely complex shapes, depending upon the particulars of the system.

The fold catastrophe model posits an attractor that looks like this figure, which I have more or less re-created from Scheffer et al. (2009), Box 1.

foldThe solid parts of the curve are stable — when the system state is perturbed when in the vicinity of this part of the attractor, it tends to return, as indicated by the grey arrows pointing back to the attractor.  The dashed part of the attractor is unstable — perturbations in this neighborhood tend to move away from the attractor.  This graphical representation of the system makes it pretty easy to see how a small perturbation could dramatically change the system if the current combination of conditions and system state place the system on the attractor near the neighborhood where the attractor changes from stable to unstable.  The figure illustrates one such scenario.  The conditions/system state start at point F1. A small forcing perturbs the system off this point across the bifurcation.  Further forcing now moves the system way off the current state to some new, far away, stable state.  We go from a very high value of the system state to a very low value with only a very small change in conditions.  Indeed, in this figure, the conditions remain constant from point F1 to the new value indicated by the white point — just a brief perturbation was sufficient to cause the drastic change.  I guess this is part of the definition of a catastrophe.

The real question in my mind, and one that others have asked, is how relevant is the fold catastrophe model for real systems?  This is something I’m going to have to think about. One thing that is certain is that this is a pedagogically very useful approach as it makes you think… and worry.

On Freeman Dyson's Climate-Change Skepticism

A nice piece by Nicholas Dawidoff in the New York Times Magazine this week details the eminent physicist Freeman Dyson’s skepticism about the dangers of global warming. It seems that Mr. Dyson is concerned about the quality of the science that underlies the current scientific consensus about its perils.

One gathers from reading the Dawidoff piece that the major criticism Dyson levies climate science is against the computer models of Earth’s climate that provide much of the information we have about how Earth will respond to increased atmospheric concentrations of carbon dioxide and other greenhouse gasses (these increases are a fact that is not in dispute). The rub of planetary science is that planet-scale experiments are (for now) impossible (I think we have a way to go before the musings of Kim Stanley Robinson or Kevin J. Anderson come to pass). Our power to understand planetary processes is constrained by our N=1. There is only one Earth. It could be argued that our N is actually closer to three when you throw Venus and Mars into the mix, but the fact remains, our sample size of known planets is pretty small. My U Penn colleague David Gibson made an observation at the NAS/CNRS Frontiers of Science conference last November that studying planets is kind of like studying revolutions. I think some of the physical scientists in the room were scandalized by this vulgar analogy but I (and the other token social scientist in the room) think he made a terrific observation. In both cases, we have a very small number of relatively well-understood and, for all we know, completely eccentric cases and the poverty of this sample makes generalization highly problematic.

So what are our options for studying Earth’s climate other than computer models? I wholeheartedly agree that science is jeopardized whenever the scientist falls in love with his or her model. But there are, in fact, lots of models and these models are run by lots of independent groups emphasizing different aspects of the global circulation system in their particular specifications. It’s almost like science, actually. When one model makes an outlandish prediction, I don’t pay much attention. When all the models make that same outlandish prediction, I pay attention to it, no matter how crazy it might be. Note that this does not mean it’s correct. It does mean that the result merits attention.

Mr Dyson, it seems, thinks that global warming is a good thing. Increased atmospheric concentration of CO2 will increase plant productivity. At the very least, all we need to do to ameliorate putative negative effects of increased CO2 would be to plant lots (and lots) of super carbon-scrubbing trees (which apparently are just waiting to be genetically engineered). There are quite a few problems with this proposal. First, it is actually not completely clear that increases in CO2 will globally increase plant productivity. Ask a plant ecologist and she will tell you that there are other things that limit plant growth than CO2 (e.g, water, nitrogen, phosphorus, etc.). Then there is the fact that ecological enrichment experiments very frequently lead to decreases in biodiversity. Plants that are very good competitors for a particular resource thrive at the expense of plants that are not good competitors for that resource (but might be superior along other dimensions). There are lots of other issues that complicate the seemingly simple relationship between CO2 concentration and productivity such as an increase in ground-level ozone, ocean acidification, and the fact increased temperatures can reduce production independent of CO2 concentration. For someone who is so critical of sloppy science, it seems that Mr. Dyson needs to bone up a bit on his physiological ecology.

Dawidoff quotes Dyson as saying that ‘Most of the evolution of life occurred on a planet substantially warmer than it is now.’ Of course, the rub is that humans evolved in a cool planet. Many of the major events that have characterized the evolution of our species are thought to have involved cooling and drying (e.g., see the work of Steven Stanley or Elizabeth Vrba). What brought the first hominins out of the forest to walk bipedally across the entire planet? Probably climatic cooling and drying which broke tropical forests in Africa up into savanna mosaics. There is a very real sense in which humans are the cold-adapted ape.  I have little doubt that life of some sort will continue even in the most nightmarish of climate-change scenarios. The more parochial question that I think most people care about is: what about human life? An important addendum to this question is: what about the life that we care about?

I applaud Dyson’s contempt for orthodoxy and I admit a dis-ease that I feel among global-warming zealots. The problem with this particular windmill that he has chosen to tip at is that there are powerful economic and political interests that seek to subvert whatever good science is done in global change research for their own ends. Dyson ends up abetting the disinformationists and thereby supporting a much deeper orthodoxy than that of the marginalized community of scientists. This deeper orthodoxy is, of course, the neoliberal ideology that market forces are always preferred to scientifically-informed regulation, pecuniary reward always trumps gains in any other value system, growth-above-all, lie back and think of mother England, etc.

I think that zealotry is spawned by the difficulty of being taken seriously, especially when truth is, well, inconvenient. The loud and persistent mouths of activists are what keep ideas in the public consciousness. Global warming and its consequences are of the sort of scale that they are all too easily ignored. But I fear (and many other scientists share this fear) that we ignore the problem at our peril.

Speaking as someone who typically has an infantile response to group-think, my guess is that Dyson hangs around with a select crowd. In places like Princeton, NJ or Cambridge, MA or Palo Alto, CA, it’s easy to get the impression that everyone is a raving environmentalist (or at least wants others to think they are — a subject for a later post). I am reminded of the probably apocryphal (but so canny) story of the befuddled Democrat (Hollywood screen-writer, Manhattan socialite, Cambridge intellectual — I’ve heard versions using each), incredulous that Nixon could have won the 1972 election in a landslide, who uttered the immortal line, “but everyone I know voted for McGovern!” It’s all too easy in university towns like these to lose track of the fact that most people don’t really give a damn about global warming (or, while we’re at it, poverty, nuclear proliferation or science) and won’t until it has an undeniable impact on their lives. To see that acute concern over the impacts of global warming is not really part of some grand orthodoxy, perhaps Mr. Dyson should spend some time at the Heritage Foundation, Cato Institute, or, for that matter, just about any town in the United States besides Princeton!

A big part of Dyson’s critique, it seems, is that we don’t have enough information. Given the intractability of global experiments and a general discontent with general circulation models, we are going to need to live with a considerable amount of uncertainty. Harvard economist Martin Weitzman has written a very thought-provoking (and technically demanding) paper on the subject of cost-benefit analysis in the context of global climate change. He refers to the climate change situation as one characterized by “deep structural uncertainty.”  In a follow-up paper (in which he responds to criticisms from Yale economist, William Nordhaus), Weitzman makes the astute observation that inductive science is of limited utility when the object of study is an extremely rare event.  The world has not seen atmospheric concentrations of CO2 like what we will see in the near future in a very long time (at least 800,000 years) and we really know very little about such a world. It is very, very difficult to scientifically study extremely rare events.  This is the basis of our deep structural uncertainty and the reason that Mr. Dyson’s plea for gathering more data is unlikely to help all that much with decision-making.

Weitzman further notes that the most severely negative outcomes of global warming are unlikely.  Unfortunately, our systematic uncertainty over the likely course of atmospheric greenhouse gas accumulation, the functional response global climate to this accumulation, or the parameters of the different models of climate change means that these unlikely events are less unlikely than they would be if we knew more.  Uncertainty compounds.  (This probably merits its own blog posting but Spring Break is nearly over…) The probability distribution of future outcomes is “fat-tailed.” This means that the probability of truly catastrophic outcomes is not trivial.  A “long-tailed” distribution means that extreme events are possible but only vanishingly probable.  A fat-tailed distribution means that unlikely events are more likely than we might be comfortable with. Weitzman concludes that, given the fat tail of outcomes-of-global-warming distribution, a sensible cost-benefit analysis favors strong action to mitigate the future effects of this looming problem.

It’s such a shame that a man of science of the stature of Freeman Dyson is spending his time (apparently) unwittingly abetting the cause of anti-science and the neoliberal status quo. In contrast, I find Weitzman’s perspective very sensible indeed.  When we put our egos aside, we have to acknowledge the fact that there is huge amount of — probably intractable — uncertainty surrounding the future of global warming.  When there is a small (but non-trivial) probability of a catastrophic event, does it not seem prudent to take steps to avoid catastrophe? 

 

Many Americans Believe That Global Warming is "Exaggerated"

Results from a recent Gallup poll are rather depressing. Based on telephone interviews with a sample of 1,012 Americans, more Americans think that the reporting on global warming is exaggerated than think its seriousness is under-estimated (41% vs. 28%).  This looks like a real change since it wasn’t that long ago (2006) that the numbers were reversed. Political party affiliation helps predict how people feel about global warming. Nearly two-thirds of self-reported Republican respondents (66%) think that news reports on global warming are exaggerated.  This is up from 35% in 1998, when Gallop started surveys on global warming. 

It seems likely that the economic crisis has blunted people’s concern over global warming.  Lydia Saad, the author of the Gallup press release writes,

Importantly, Gallup’s annual March update on the environment shows a drop in public concern about global warming across several different measures, suggesting that the global warming message may have lost some footing with Americans over the past year. Gallup has documented declines in public concern about the environment at times when other issues, such as a major economic downturn or a national crisis like 9/11, absorbed Americans’ attention. To some extent that may be true today, given the troubling state of the U.S. economy. However, the solitary drop in concern this year about global warming, among the eight specific environmental issues Gallup tested, suggests that something unique may be happening with the issue.

One wonders what exactly is going on to make Americans specifically less concerned about global warming…

Cool Interview with Michael Pollan

Yale e360 Magazine has a very interesting interview with author, Michael Pollan ( “Eat food. Not too much. Mostly plants” ) on what’s wrong with environmentalism. Not surprisingly, much of the conversation surrounds food production and its environmental impacts.  I find the discussion of the energy crisis of the 1970s — and how badly we have fallen away from our practical responses to it — particularly poignant.