Resilience Thinking and a Decision-Analytic Approach to Conservation: Strange Bedfellows or Essential Partners?

Abstract

ABSTRACT. There has been some tendency to view decision science and resilience theory as opposing approaches, or at least as contending perspectives, for natural resource management. Resilience proponents have been especially critical of optimization in decision science, at least for those cases where it is focused on the aggressive pursuit of efficiency. In general, optimization of resource systems is held to reduce spatial, temporal, or organizational heterogeneity that would otherwise limit efficiency, leading to homogenization of a system and making it less able to cope with unexpected changes or disturbances. For their part, decision analysts have been critical of resilience proponents for not providing much practical advice to decision makers. We believe a key source of tension between resilience thinking and application of decision science is the pursuit of efficiency in the latter (i.e., choosing the "best" management action or strategy option to maximize productivity of one or few resource components), vs. a desire in the former to keep options open (i.e., maintaining and enhancing diversity). It seems obvious, however, that with managed natural systems, there must be a principle by which to guide decision making, which at a minimum allows for a comparison of projected outcomes associated with decision alternatives. This is true even if the primary concern of decision making is the preservation of system resilience. We describe how a careful framing of conservation problems, especially in terms of management objectives and predictive models, can help reduce the purported tension between resilience thinking and decision analysis. In particular, objective setting in conservation problems needs to be more attuned to the dynamics of ecological systems and to the possibility of deep uncertainties that underlie the risk of unintended, if not irreversible, outcomes.Resilience thinking also leads to the suggestion that model development should focus more on process rather than pattern, on multiple scales of influence, and on phenomena that can create alternative stability regimes. Although we acknowledge the inherent difficulties in modeling ecological processes, we stress that formulation of useful models need not depend on a thorough mechanistic understanding or precise parameterization, assuming that uncertainty is acknowledged and treated in a systematic manner.

Making decisions for managing ecosystem services

“…Fundamental to ecosystem service assessments is an understanding of both the social and ecological context (Johnson et al, 2013;Reyers et al, 2013). According to the literature reviewed, ecosystem services research has incorporated a variety of ecological, social, abiotic, land use, and economic data (Fig.…”

Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

“…The ecosystem management literature in general, and analyses of the lake problem in particular, focus on the economic value represented through the maximization of expected utility (MEU) as the sole objective to evaluate alternative strategies , Maler et al 2003, Bond 2010, Horan et al 2011, Johnson et al 2013. These standard approaches position themselves in the lower left side of Figure 1.…”

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

“…Although a number of researchers have begun to formulate models that can be used to explore properties of resilience [78][79][80], more needs to be done to develop models that can be used to provide practical advice for those concerned with ecosystem management. We believe that a useful approach will be to use the described methods of decision analysis, but to modify objectives (stressing outcomes that are robust) and models in a manner consistent with resilience ideas [81].…”