Environmental Modeling & Assessment

, Volume 16, Issue 1, pp 15–36 | Cite as

Confronting Management Challenges in Highly Uncertain Natural Resource Systems: a Robustness–Vulnerability Trade-off Approach

  • Armando A. Rodriguez
  • Oguzhan Cifdaloz
  • John Martin AnderiesEmail author
  • Marco A. Janssen
  • Jeffrey Dickeson


This paper presents a framework for the study of policy implementation in highly uncertain natural resource systems in which uncertainty cannot be characterized by probability distributions. We apply the framework to parametric uncertainty in the traditional Gordon–Schaefer model of a fishery to illustrate how performance can be sacrificed (traded-off) for reduced sensitivity and hence increased robustness, with respect to model parameter uncertainty. With sufficient data, our robustness–vulnerability analysis provides tools to discuss policy options. When less data are available, it can be used to inform the early stages of a learning process. Several key insights emerge from this analysis: (1) the classic optimal control policy can be very sensitive to parametric uncertainty, (2) even mild robustness properties are difficult to achieve for the simple Gordon–Schaefer model, and (3) achieving increased robustness with respect to some parameters (e.g., biological parameters) necessarily results in increased sensitivity (decreased robustness) with respect to other parameters (e.g., economic parameters). We thus illustrate fundamental robustness–vulnerability trade-offs and the limits to robust natural resource management. Finally, we use the framework to explore the effects of infrequent sampling and delays on policy performance.


Resource management Uncertainty Robust control Policy implementation Learning Vulnerability 



The authors would like to thank Elinor Ostrom, William Brock, Charles Perrings, and Ann Kinzig for helpful comments on earlier drafts of this manuscript.


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Armando A. Rodriguez
    • 1
  • Oguzhan Cifdaloz
    • 2
  • John Martin Anderies
    • 2
    Email author
  • Marco A. Janssen
    • 2
  • Jeffrey Dickeson
    • 1
  1. 1.Intelligent Embedded Systems Laboratory (IeSL), Department of Electrical EngineeringArizona State UniversityTempeUSA
  2. 2.School of Human Evolution and Social ChangeArizona State UniversityTempeUSA

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