Overview
- Authors:
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James N. Kremer
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Department of Biological Sciences, University of Southern California, Los Angeles, USA
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Scott W. Nixon
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Graduate School of Oceanography, University of Rhode Island, Kingston, USA
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Table of contents (12 chapters)
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Perspectives
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- James N. Kremer, Scott W. Nixon
Pages 1-13
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The Narragansett Bay Model
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- James N. Kremer, Scott W. Nixon
Pages 14-19
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Theoretical Formulations
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- James N. Kremer, Scott W. Nixon
Pages 23-36
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- James N. Kremer, Scott W. Nixon
Pages 37-59
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- James N. Kremer, Scott W. Nixon
Pages 60-90
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- James N. Kremer, Scott W. Nixon
Pages 91-103
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Simulation and Analysis
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Front Matter
Pages 105-105
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- James N. Kremer, Scott W. Nixon
Pages 107-125
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- James N. Kremer, Scott W. Nixon
Pages 126-130
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- James N. Kremer, Scott W. Nixon
Pages 131-163
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- James N. Kremer, Scott W. Nixon
Pages 164-176
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- James N. Kremer, Scott W. Nixon
Pages 177-192
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- James N. Kremer, Scott W. Nixon
Pages 193-199
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Back Matter
Pages 200-220
About this book
One aim of the physical sciences has been to give an exact picture of the material world. One achievement of physics in the twentieth century has been to prove that that aim is unattainable . . . . There is no absolute knowledge. And those who claim it, whether they are scientists or dogmatists, open the door to tragedy. All information is imperfect. We have to treat it with humility. Bronowski (1973) The Ascent of Man It seems particularly appropriate to us to begin this book with Jacob Bronowski's passionate message firmly in mind. Those who set out to construct numerical models, especially ones that are mechanistic and essentially deterministic, must work always with this awareness as a backdrop for their efforts. But this is also true for the most meticulous physiologist or observant naturalist. We are all dealing with simplifications and abstractions, all trying to figure out how nature works. Unfortunately, this common pursuit does not always lead to mutual understanding, and we have become increasingly aware over the past six years that many ecologists feel a certain hostility or at least distrust toward numerical modeling. In a number of cases the reasons for such feelings are personal and very understandable-hardยญ gotten data skimmed off by someone with little appreciation for the difficulties involved in obtaining reliable measurements, grandiose claims of predictability, the tendency for some model builders to treat other scientists as number-getters whose research can be directed in response to the needs of the model, etc.
Authors and Affiliations
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Department of Biological Sciences, University of Southern California, Los Angeles, USA
James N. Kremer
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Graduate School of Oceanography, University of Rhode Island, Kingston, USA
Scott W. Nixon