Integrating Subjective and Objective Dimensions of Resilience in Fire-Prone Landscapes

Abstract

Resilience has become a common goal for science-based natural resource management, particularly in the context of changing climate and disturbance regimes. Integrating varying perspectives and definitions of resilience is a complex and often unrecognized challenge to applying resilience concepts to social-ecological systems (SESs) management. Using wildfire as an example, we develop a framework to expose and separate two important dimensions of resilience: the inherent properties that maintain structure, function, or states of an SES and the human perceptions of desirable or valued components of an SES. In doing so, the framework distinguishes between value-free and human-derived, value-explicit dimensions of resilience. Four archetypal scenarios highlight that ecological resilience and human values do not always align and that recognizing and anticipating potential misalignment is critical for developing effective management goals. Our framework clarifies existing resilience theory, connects literature across disciplines, and facilitates use of the resilience concept in research and land-management applications.

Keywords: adaptation; ecological resilience; social resilience; social–ecological systems; wildfire; wildland.

Figure 1.

The value-free—value-explicit framework and archetypical scenarios. The conditions are characterized by their probability (x-axis) and acceptability (y-axis) of a state change after a disturbance such as wildfire. The probability of a state change is inversely correlated with resilience. The acceptability of a state change is a social evaluation of whether stakeholders prefer to shift to an alternative condition and is inversely correlated to the desirability of the current condition. The traditional ball-and-cup diagrams (sensu Holling 1973) illustrate greater resilience with deeper cups. The dotted lines indicate the desired postdisturbance trajectory, with arrow length proportional to the energy required for recovery. The panels’ shading indicates a threat level with respect to the probability and acceptability of state change (increasing from green, yellow, orange, to red). Finally, the location of a system in any quadrant reflects a snapshot in time and should be routinely reassessed as the system changes over time.

Figure 2.

Probability of state change (x) as a function of acceptability of state change (y) for components in a hypothetical social–ecological system. The horizontal error bars represent the hypothetical lack of precision in estimating the probability of a state change, whereas the vertical error bars correspond to the hypothetical diversity of subjective evaluations among stakeholders, with narrower bars reflecting higher levels of consensus. For example, stakeholder agreement may be higher for components affecting water quality than for those affecting timber-related jobs. The specific components evaluated would vary among different SESs. Abbreviation: T&E, threatened and endangered species.

Figure 3.

Examples of changing system conditions and social acceptability over time, after a fire occurs. Three general scenarios are considered, illustrated by the ball-and-cup diagrams in the grey boxes below the x-axis, each with one or more example(s) (i.e., photograph insets above each scenario). All examples inherently start at 0 on the x-axis; the thin grey dashed line half way along the y-axis represents neutral acceptability (as in figures 1 and 2). An end point of 0 on the x-axis indicates a return to the prefire state (i.e., recovery), whereas a value of 1.0 indicates a state change; each dash in the thick dashed lines represents approximately uniform time increments, indicating faster (e.g., a, b) or slower (e.g., c) rates of change. (a) Relatively rapid recovery after a low-severity surface fire in a ponderosa pine forest (photograph: Metolius NRA, USFS) and after (b) an invasive-grass-fueled fire in sage steppe (photograph: USDA/NRCS); in both cases, there is little fire-caused change in the system or in social acceptability of the condition. (c) Slow postfire recovery after a high-severity, stand-replacing fire in subalpine forest, illustrated immediately after fire, and along the trajectory to recovery (photographs: Brian J. Harvey). As the system recovers, social acceptability of the system state increases; the thick, grey dashed line illustrates the potential for managers to accelerate postfire recovery and social acceptability. (d) Potential conversion from forest to nonforest state after a large, high-severity fire in dry mixed-conifer forest (Photograph: USGS/Craig D. Allen). The question mark indicates an uncertain trajectory and potential for a state change.