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

Abstract

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.

Ecohydrological modeling in agroecosystems: Examples and challenges

“…We also tried to frame the problem of soil and water resources management using the theory of optimal stochastic control (section 4). Here the challenge of including multiple objectives or constraints dealing with sustainability and profitability that necessarily involve human factors is again compounded by the fact that these problems often involve uncertainties in the system's parameters and forcings, thus requiring so‐called robust control techniques to make the cost functionals relatively insensitive to fluctuations [ Anderies et al ., ; Rodriguez et al ., ]. Along these lines, the methods of uncertainty quantification [ Tartakovsky , ] may add relevant avenues of both theoretical and applied research.…”

The control versus resilience rationale for managing systems under uncertainty

“…The scope of application rapidly expanded to diverse types of systems in various fields (Miser and Quade 1988), such as economics, policy and decision analysis (Raiffa 1968, Dunn 2008) and natural resources management (Reed 1979, Clark and Kirkwood 1986, Margules and Sarkar 2007. More recently, for intrinsically uncertain systems, the optimal control approach is often replaced by a focus on robust control , Rodriguez et al 2011. Robust control seeks to identify policies that are robust to model misspecifications, i.e., perform well over a set of possible models and input ranges, thus accounting for uncertainties.…”

“…According to Anderies et al (2006), the theory of optimization served well in the early development phase of resource use industries, but we need to move on to an era in which something like a resilience framework forms the basis for policy and management. The application of robust control theory , Rodriguez et al 2011, methods to analyse control of dynamic systems using viability theory (Martin 2004, Rougé et al 2013, optimization techniques for resilience concepts (e.g. Van den Bergh 2008) and methods for robust decision-making (Polasky et al 2011) provide attempts to reconcile the two rationales, but until date there remains a schism between control for-resilience approaches (integrating goals of resilience under the control approach) and replace-control-by-resilience approaches.…”

Applying resilience thinking to production ecosystems

“…v www.esajournals.org In addition, the potential pitfalls of sustained coerced resilience have similarities with the concepts of 'robustness' and 'robust control', which have been used to explain potential fragilities or dysfunctions within complex systems (Csete and Doyle 2002, Anderies et al 2007, Doyle and Csete 2011, including within a resource management context (e.g., Cifdaloz et al 2010, Rodriguez et al 2011 Given the cross-boundary interactions detailed above, supporting and recipient systems, as well as the production system themselves, may be jeopardized in the face of ongoing human intervention to maximize production ( Fig. 4).…”