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Useless Arithmetic: Why Environmental Scientists Can't Predict the Future
     

Useless Arithmetic: Why Environmental Scientists Can't Predict the Future

4.3 3
by Orrin H. Pilkey
 

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Noted coastal geologist Orrin Pilkey and environmental scientist Linda Pilkey-Jarvis show that the quantitative mathematical models policy makers and government administrators use to form environmental policies are seriously flawed. Based on unrealistic and sometimes false assumptions, these models often yield answers that support unwise policies.

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Overview

Noted coastal geologist Orrin Pilkey and environmental scientist Linda Pilkey-Jarvis show that the quantitative mathematical models policy makers and government administrators use to form environmental policies are seriously flawed. Based on unrealistic and sometimes false assumptions, these models often yield answers that support unwise policies.

Writing for the general, nonmathematician reader and using examples from throughout the environmental sciences, Pilkey and Pilkey-Jarvis show how unquestioned faith in mathematical models can blind us to the hard data and sound judgment of experienced scientific fieldwork. They begin with a riveting account of the extinction of the North Atlantic cod on the Grand Banks of Canada. Next they engage in a general discussion of the limitations of many models across a broad array of crucial environmental subjects.

The book offers fascinating case studies depicting how the seductiveness of quantitative models has led to unmanageable nuclear waste disposal practices, poisoned mining sites, unjustifiable faith in predicted sea level rise rates, bad predictions of future shoreline erosion rates, overoptimistic cost estimates of artificial beaches, and a host of other thorny problems. The authors demonstrate how many modelers have been reckless, employing fudge factors to assure "correct" answers and caring little if their models actually worked.

A timely and urgent book written in an engaging style, Useless Arithmetic evaluates the assumptions behind models, the nature of the field data, and the dialogue between modelers and their "customers."

Editorial Reviews

American Scientist - Carl Wunsch
This book is a welcome antidote to the blind use of supposedly quantitative models.
New Scientist - Fred Pearce
This is an easy and persuasive read.
Issues in Science and Technology - Steven R. Carpenter
A concise, powerful, and readable book.
BioScience - David Simberloff
Useless Arithmetic will surely excite any reader.
Choice
This book should be in every library... Essential.
The Midwest Book Review
Useless Arithmetic dispels many myths and is a 'must read' packing in case studies and insights on faulty thinking.
Earth Island Journal
[This] readily accessible book should be read by any activist who's ever had to face off against the opposition's engineers.
Library Journal
Environmental models are critical to understanding and predicting natural phenomena. Geologists Pilkey (emeritus, Duke Univ. Sch. of the Environment; A Celebration of the World's Barrier Islands) and Pilkey-Jarvis (department of ecology, Washington State) have written a fascinating book on the issues surrounding the mathematical models used to formulate environmental policies. To reflect better the book's content, its title should be Environmental Policies and Mathematical Models: Reliability, Issues, and Case Studies. The authors discuss the relevance of mathematical modeling as a means to predict future large, complex, and evolving environmental issues; chapters as case studies explore such issues of regional and global importance as invasive species, groundwater contamination, beach erosion, global warming and rising sea levels, underground storage of nuclear waste, and depleted ocean fish stocks. The strongest sections address the history and development of environmental issues central to understanding the reliability, appropriateness, and assumptions behind modeling behavior. Written for nonspecialists, this book is devoid of mathematics and easy to read, yet it includes a limited number of pictures, notes, references, and figures. Recommended for all undergraduate academic libraries supporting environmental and ecology programs.-Ian D. Gordon, Brock Univ. Lib., St. Catharines, Ont. Copyright 2006 Reed Business Information.
Issues in Science and Technology
A concise, powerful, and readable book.

— Steven R. Carpenter

BioScience
Useless Arithmetic will surely excite any reader.

— David Simberloff

American Scientist
This book is a welcome antidote to the blind use of supposedly quantitative models.

— Carl Wunsch

New Scientist
This is an easy and persuasive read.

— Fred Pearce

Product Details

ISBN-13:
9780231132121
Publisher:
Columbia University Press
Publication date:
01/02/2007
Pages:
248
Product dimensions:
6.30(w) x 9.10(h) x 1.00(d)
Age Range:
18 Years

Read an Excerpt

The reliance on mathematical models has done tangible damage to our society in many ways. Bureaucrats that don't understand their limitations often use modeled predictions … agencies that depend upon project approvals for their very survival (such as the U.S. Army Corps of Engineers) can and frequently do find ways to adjust models to come up with correct answers that will ensure project funding. Most damaging of all is the unquestioning acceptance of the models by the public because they are assured that the modeled predictions are the state-of-the-art way to go."-from Useless Arithmetic

What People are Saying About This

Naomi Oreskes
Orrin H. Pilkey and Linda Pilkey-Jarvis argue that many models are worse than useless, providing a false sense of security and an unwarranted confidence in our scientific expertise. Regardless of how one responds to their views, they can't be ignored. A must-read for anyone seriously interested in the role of models in contemporary science and policy.

Daniel Sarewitz
In a complex, imperfect world quantitative models feed the delusion that society can predict its way out of its environmental dilemmas. The corrosive result is that politics and science have become inextricably interwoven to the considerable detriment of both. This engaging, wise, and far-reaching book diagnoses the causes and costs of our quantitative hubris, and in so doing points the difficult way toward a more productive relationship among science, democracy, and the vexing challenges of environmental stewardship.

Ron Brunner
Useless Arithmetic is an important book for those of us who believe that environmental science and policy should be self-correcting on the basis of experience. Written for lay persons, it draws attention to a broad range of sobering experiences typically ignored in the over-promotion of quantitative models for predictive purposes.

Victor R. Baker
Using concrete examples, the authors of Useless Arithmetic cut through the scientific jargon to show how and why many aspects of the environment are under threat because of the slavish adherence to misleading mathematical models by their technical and political advocates.

Meet the Author

Orrin H. Pilkey is the James B. Duke Professor of Geology emeritus and director emeritus of the Program for the Study of Developed Shorelines at Duke University's Nicholas School of the Environment. He has written numerous books, including A Celebration of the World's Barrier Islands, and is the editor of the twenty-four-volume series, Living with the Shore.Linda Pilkey-Jarvis is a geologist in the State of Washington's Department of Ecology, where she helps manage the state's oil spills program.

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Useless Arithmetic: Why Environmental Scientists Can't Predict the Future 4.3 out of 5 based on 0 ratings. 3 reviews.
plappen More than 1 year ago
Government administrators and policy makers use quantitative mathematical models to form future environmental policies. The authors of this book assert that these models are basically useless, that they lead to policies that make things worse, not better. These models are filled with assumptions, suppositions and several pure guesses. "Fudge factors" are included to come up with an acceptable answer. Politics is frequently involved. An example is when the Canadian government said that the Grand Banks fishing area was in good condition, when "collapse" was a much more accurate description. The EPA has required that the Yucca Mountain nuclear waste disposal site must be safe for the public for the next 10,000 years. Based on current models, that is absurd enough, but, in 2004, a federal appeals court ruled that the safety of the repository must be assured for up to one million years. Really? That is longer than Homo Sapiens has existed, and there will be at least one major advance and retreat of glaciers, with corresponding huge changes in climate. Open pit mines are frequently dug beneath the level of the local groundwater. Constant pumping of water keeps the mine dry. When the mine is abandoned, the local water, filled with all sorts of chemicals from the mine, fills the pit. How to predict things like the balance between inflow and outflow of water from the lake, acid production, and chemical reactions within the new lake? Perhaps it would be better to say, for instance, "Given current conditions, the ocean level will rise over the next hundred years" instead of "Given current conditions, the ocean level will rise by (a specific number) over the next hundred years." Researchers freely admit that the models are full of flaws, but, until someone comes up with something better, they will continue to use them. Written for the non-scientist (like yours truly), this book is very thought-provoking, and injects some much needed skepticism. It's a must-read of a book.
Anonymous More than 1 year ago
Guest More than 1 year ago
I highly recommend this book for engineers and modelers of natural systems who have dwelled too long in the world of fabricated realities and conflicted interests. You may not agree with everything the Pilkeys say - I didn't - but the book is sure to take off your rose-colored glasses and get your feet headed back towards the ground. This book encourages me, an ecologist who analyzes estuarine monitoring data, to keep questioning the assumptions and 'data' of fisheries and ecosystem models.