At first glance, it is odd to single out environmental scientists for being unable to predict the future. However, like stock pickers, some preachers and electoral pollsters, environmental scientists do make a business of predicting the future.
Not one of these groups has had any success, but it is arguable that the environmental scientists have done the most damage to other people by being wrong.
Orrin Pilkey, a well-known if not always well-liked specialist on coastal processes at Duke, began a seminar to examine why the predictions of coastal engineers seemed so often to lead to projects that didn't work. (I have known the North Carolina beaches where Pilkey does much of his work for more than 50 years. The Outer Bankers hate what Pilkey says about their beaches, but he's right.)
The investigation led to a wider examination of numerical models of all sorts of natural processes. Among those examined -- all failures -- were managing the Grand Banks fishery, predicting the lifetime of nourished beaches, predicting toxicity of lakes in abandoned pit mines and predicting how fast sea level will rise. Predictably, more attention is paid to coastal processes than anything else, but other topics get fair treatment, even one as far from the coast as the Yucca Mountain atomic waste dump.
What the Pilkeys found was no surprise to me as a newspaper reporter, and will be even less a surprise to scientists. People forget, but reporters keep clipping files. Mine contain many reminders about predictions made but unfulfilled. The Pilkeys conclude that it is impossible to write quantitative numerical models of any complex process on the surface of the earth. This is unlike numerical models of tractable systems, like the orbits of comets or the fracture strength of a steel-frame building.
For most people, the most familiar such models are the global circulation models used by the Intergovernmental Panel on Climate Change to predict catastrophic global warming. The Pilkeys barely mention GCMs in passing, and this is probably wise. If their goal is to get non-technical people (or even technical people with open minds about modeling) to rethink the enthusiasm for them, then injecting global warming into the mix would no doubt distract from their greater goal.
However, the deduction is clear and inescapable -- forget the GCMs. They offer no guide to anything.
The reasons all these models fail are many. One the Pilkeys emphasize more than any other is the "ordering problem." Even if you knew all the parameters that count (seldom or never the case), and even if you knew how they interact with each other), you can never, ever know in which order the variable ones will present themselves. If current changes affect beaches and hurricanes affect beaches, and both are variable over time, you cannot know in advance whether the storm will come first, or something will alter the current first.
This is not an original thought. Although he did not call it an ordering problem, the immunologist and philosopher of science Peter Medawar identified it as the reason that it will always be impossible to conduct meaningful experiments to disentangle the effects of nature and nurture on human behavior. (See his essay, "Further Comments on Psychoanalysis" in "The Strange Case of the Spotted Mice" and my review of that book.)
Other critics, such as Vaclav Smil and Naomi Oreskes, have also demolished the concept of numerical modeling of complex systems, and the Pilkeys give them credit for their work. Even outside the natural sciences, the empirical failure of attempts to predict (or even to quantify) complex systems have been demonstrated conclusively, for instance by lawyer Michael Wheeler in "Lies, Damn Lies and Statistics: the Manipulation of Public Opinion in America." That book was published more than 30 years ago; there really can be no excuse at this late date for people to question the Pilkeys' conclusion.
People do. Orrin Pilkey has been called a neo-Luddite by defenders of quantitative modeling.
The beaches, however, are not there, just as he said they would not be.
As an alternative, the Pilkeys advocate qualitative modeling. It gives, at best, trends, it outlines areas that might require remediation as things develop. Its asset is flexibility. That's something you never get with a seawall. Those are inflexible.
Another approach, about which the Pilkeys take no firm stand, is the Dutch method of dealing with retreating beaches: dump and run. In other words, build up the beach without expectations of how soon it will have to be done again. The Dutch, with their heritage of centuries of battling the sea, probably think in terms of processes rather than "solutions."
This short but powerful volume is explicitly aimed at non-technical readers. Although quantitative models are mathematical, it is not necessary to know math to understand how they work, and the Pilkeys relegate what little math is in the book to an appendix. Like Orrin Pilkey's lectures to public audiences on coastal erosion, he can make complex processes understandable, if not predictable.
I only wish the Pilkeys had included a chapter on wellhead protection zones, which are going to become an increasingly hot topic in many areas. These attempt to predict how far you have to keep pollutant sources away from the places you find your drinking water. The approach used so far has been numerical modeling. "Useless Arithmetic" does not encourage confidence in the protection policies being adopted.