This is not to say that analytical models cannot be useful in other ways—for example, it would seem that comparing model predictions to subsequent observations could help scientists understand a phenomenon better. Not necessarily so, according to the authors of Useless Arithmetic, who argue that beach nourishment, shoreline erosion, and mine-pit water models have not done even that. In these and other fields, reification of model variables has, in their view, not only led to unjustified policy decisions but also discouraged the gathering of empirical data that would enhance scientific understanding.
Useless arithmetic: why environmental scientists can't predict the future
In contrast to those areas, the use of models in plant invasions is exemplary, Pilkey and Pilkey-Jarvis point out, lauding a National Research Council report and other invasion-biology publications for being forthright about the severe limitations of predictive models and advocating caution in applying models to policy decisions.
They thus turn what is perhaps the main criticism of modern invasion biology—that it lacks a theoretical basis with quantitative, predictive, generally applicable models—into a virtue.
The chief villains in the piece, according to the authors, are engineers, and they see it as no coincidence that the National Research Council committee on predicting plant invasions consisted wholly of academic scientists—it had no engineers. Modeling in the other fields, except for fisheries and global sea-level change, is dominated by engineers.
- Useless arithmetic: why environmental scientists can't predict the future | Awards & Grants.
- An Introduction to Gardening.
- Subscribe Now!
- Angry Indictment of Mathematical Modeling | BioScience | Oxford Academic.
- Useless Arithmetic: Why Environmental Scientists Can't Predict the Future.
- Useless Arithmetic: :: Earth Island Journal.
Pilkey and Pilkey-Jarvis believe that the very nature of engineering models renders the models incapable of adequately representing the complexity and stochasticity of many environmental phenomena. Concrete and steel structures are immeasurably simpler than the physical and biological processes that operate all over Earth. For a particularly good example of political pollution, consider how quantitative models abetted the collapse of the Canadian cod fishery. This is a very angry book. Like Michael Crichton , the authors accuse global-change modelers of being concerned primarily with their own funding.
They call the coastal engineering profession a disgrace. They say the field of pit-lake chemistry is in a woeful state. They label much of the mathematical modeling community an unassailable and untouchable priesthood that, by virtue of being a priesthood, has avoided the criticism and debate that characterize normal science. They attack prominent approaches to policy-relevant modeling, such as meta-analysis and cost-benefit analysis. They regard many of the costly, even disastrous failures of military policies as the results of bad modeling.
And they name names, identifying many of the villains in the fields they criticize and detailing their sins. The authors go so far as to open themselves to the charge of settling scores, quoting from critical reviews of a rejected manuscript of the senior author, and assailing the journal to which the paper was submitted and its editors. The vitriol is sufficiently stark and unrelenting that a casual reader, with no expertise in the specific fields under discussion, might suspect the book is the work of neo-Luddites an epithet Pilkey proudly admits to having been called by one of the coastal engineers he criticizes.
For readers who are scientists, the authors do not help themselves by striving to present their criticism of mathematical models wholly verbally, with almost no equations except for those in an appendix that presents several beach models. Further, they could have clarified their case for both scientists and lay readers with several straightforward, definitional treatments. Nor do they describe exactly the differences between engineering and science, which they see as a crucial component of the issues they discuss.
Similarly, their definition of adaptive management is informal and incomplete and does not address the substantial published criticisms of this approach to resource management e. And yet, this is a compelling book, hard to put down and impossible to dismiss on the merits of the case.
Useless Arithmetic: Why Environmental Scientists Can't Predict the Future by Orrin H. Pilkey
The authors often score telling points, as when they show how standard coefficients in equations widely used to decide policy are often only fudge factors to make the equations produce a desired answer. Similarly, the details of many disasters make for gripping reading: The discussion of why a discredited model of shoreline retreat with sea-level rise—the Bruun rule—continues to be widely used is perceptive and broadly applicable to a number of environmental and ecological fields.
The authors name names, expose motivations, and suggest alternatives. The audience for this book is "non-specialists who are interested in nature and in the politics of working with the earth" page xiv. Most people I know who fit this label are environmentalists interested in understanding why our society is so bad at living with natural systems and what we can do about it. So the tone of the book is already biased, but nobody would say that it is intended to be an unbiased look at the ways that we plan and justify our interventions in natural systems.
Geographers in the southeastern U.
His documentation of the vicissitudes of beach replenishment, the very useful series of "Living with the Shore," and his more recent critiques of coastal business-as-usual are all well known to anyone interested in coasts and beaches. His co-author, Linda Pilkey-Jarvis, brings expertise in both environmental contamination problems and public administration.
Useless Arithmetic:
The pairing of a serious academic gadfly with an environmental scientist who works professionally in the public arena makes for a broad, and very useful, perspective. The book is organized around seven case studies in which quantitative mathematical modeling has been at least misleading and at worst highly damaging. Each case is described in a chapter: Project MUSE promotes the creation and dissemination of essential humanities and social science resources through collaboration with libraries, publishers, and scholars worldwide.
Forged from a partnership between a university press and a library, Project MUSE is a trusted part of the academic and scholarly community it serves.
References cited
Built on the Johns Hopkins University Campus. This website uses cookies to ensure you get the best experience on our website. Without cookies your experience may not be seamless. In lieu of an abstract, here is a brief excerpt of the content: