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Cited by 1,463

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Uncertainty, Resource Exploitation, and Conservation: Lessons from History

Ludwig, Donald, Hilborn, Ray, Walters, Carl·1993·Science

Abstract

There are currently many plans for sustainable use or sustainable development that are founded upon scientific information and consensus. Such ideas reflect ignorance of the history of resource exploitation and misunderstanding of the possibility of achieving scientific consensus concerning resources and the environment. Although there is considerable variation in detail, there is remarkable consistency in the history of resource exploitation: resources are inevitably overexploited, often to the point of collapse or extinction. We suggest that such consistency is due to the following common features: (i) Wealth or the prospect of wealth generates political and social power that is used to promote unlimited exploitation of resources. (ii) Scientific understanding and consensus is hampered by the lack of controls and replicates, so that each new problem involves learning about a new system. (iii) The complexity of the underlying biological and physical systems precludes a reductionist approach to management. Optimum levels of exploitation must be determined by trial and error. (iv) Large levels of natural variability mask the effects of overexploitation. Initial overexploitation is not detectable until it is severe and often irreversible.

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Metadata

Authors
Ludwig, D., Hilborn, R., & Walters, C.
Venue
Science
Published
1993-04-02
Volume
260
Issue
5104
Pages
17-36
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2088395296
Cited by
1,463
References
1
FWCI
259.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Uncertainty, Resource Exploitation, and Conservation: Lessons from History. https://app.cochat.ai/papers/10.1126/science.260.5104.17
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Ludwig, D., Hilborn, R., & Walters, C. (1993). Uncertainty, Resource Exploitation, and Conservation: Lessons from History. Science. https://doi.org/10.1126/science.260.5104.17

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

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