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Cited by 1,194

The DOI matches its Crossref record.

Engineering Within Ecological Constraints

·1996·National Academies Press eBooks
DOI 10.17226/4919
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Abstract

Engineering within Ecological Constraints presents a rare dialogue between engineers and environmental scientists as they consider the many technical as well as social and legal challenges of ecologically sensitive engineering. The volume looks at the concepts of scale, resilience, and chaos as they apply to the points where the ecological life support system of nature interacts with the technological life support system created by humankind. Among the questions addressed are: What are the implications of differences between ecological and engineering concepts of efficiency and stability? How can engineering solutions to immediate problems be made compatible with long-term ecological concerns? How can we transfer ecological principles to economic systems? The book also includes important case studies on such topics as water management in southern Florida and California and oil exploration in rain forests. From its conceptual discussions to the practical experience reflected in case studies, this volume will be important to policymakers, practitioners, researchers, educators, and students in the fields of engineering, environmental science, and environmental policy.

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Metadata

Venue
National Academies Press eBooks
Publisher
National Academies Press
Published
1996-03-22
DOI
10.17226/4919
OpenAlex
W1519805412
Cited by
1,194
References
0
FWCI
63.17
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Engineering Within Ecological Constraints. https://app.cochat.ai/papers/10.17226/4919
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Engineering Within Ecological Constraints. (1996). National Academies Press eBooks. https://doi.org/10.17226/4919

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.