For @theNASciences in 1996, #CSHolling clarified definitions of resilience, with engineering seeking one equilibrium state, while ecology recognizes many.
Those who emphasize the near-equilibrium definition of engineering resilience, for example, draw predominantly from traditions of deductive mathematical theory (Pimm,. 1984) where simplified, untouched ecological systems are imagined, or from traditions of engineering, where the motive is to design systems with a single operating objective (DeAngelis, 1980; O’Neill et al., 1986; Waide and Webster, 1976). On the one hand, that makes the mathematics more tractable, and on the other, it accommodates the engineer’s goal to develop optimal designs. There is an implicit assumption of global stability, that is, that only one equilibrium steady state exists, or, if other operating states exist, they should be avoided (Figure 1) by applying safeguards. [Holling 1996, pp. 33-34]
- DeAngelis, D.L. 1980. Energy flow, nutrient cycling and ecosystem resilience. Ecology 61:764-771.
- O’Neill, R. V., D. L. DeAngelis, J. B. Waide, and T. F. H. Allen. 1986. A Hierarchical Concept of Ecosystems. Princeton, N.J.: Princeton University Press .
- Pimm, S.L. 1984. The complexity and stability of ecosystems. Nature 307:321-326.
- Waide, J. B., and J. R. Webster. 1976. Engineering systems analysis: Applicability to ecosystems.
- Volume IV, pp. 329-371 in Systems Analysis and Simulation in Ecology, B.C. Patten, ed.
- New York: Academic Press.
Those who emphasize the stability domain definition of resilience (ecological resilience), on the other hand, come from traditions of applied mathematics and applied resource ecology at the scale of ecosystems. Examples include the dynamics and management of freshwater systems (Fiering, 1982), of forests (Holling et al., 1977), of fisheries (Walters, 1986), of semiarid grasslands (Walker et al., 1969) and of interacting populations in nature (Dublin et al., 1990; Sinclair et al., 1990). Because these studies are rooted in inductive rather than deductive theory formation and in experience with the impacts of large-scale management disturbances, the reality of flips from one operating state to another cannot be avoided. Moreover, it becomes obvious that the variability of critical variables forms and maintains the stability landscape (Figure 2). [Holling 1996, p. 34]
- Dublin, H. T., A. R. E. Sinclair, and J. MeGlade. 1990. Elephants and fire as causes of multiple stable states in the Serengeti-mara woodlands. Journal of Animal Ecology 59:1147-1164.
- Fiering, M.B. 1982. Alternative indices of resilience. Water Resources Research 18:33-39.
- Holling, C. S., D. D. Jones, and W. C. Clark. 1977. Ecological policy design: A case study of forest and pest management. IIASA CP-77-6:13-90 in Proceedings of a Conference on Pest Management, October 1976, G. A. Norton and C. S. Holling, eds. Laxenburg, Austria.
- Walker, B. H., D. Ludwig, C. S. Holling, and R. M. Peterman. 1969. Stability of semi-arid savanna grazing systems. Ecology 69:473-498.
- Walters, C.J. 1986. Adaptive Management of Renewable Resources. New York: McGraw Hill.
The heart of these two different views of resilience lies in assumptions regarding whether multistable states exist. If it is assumed that only one stable state exists or can be designed to so exist, then the only possible definitions for, and measures of, resilience are near-equilibrium ones—such as characteristic return time. Prod that is certainly consistent with the engineer’s desire to make things work, not to make things that break down or suddenly shift their behavior. But nature is different. [Holling 1996, p. 38]
Holling, C.S. 1996. “Engineering Resilience versus Ecological Resilience.” In Engineering Within Ecological Constraints, edited by Peter C. Schultze, 31–44. Washington, DC: National Academies Press. https://doi.org/10.17226/4919. Read online at https://www.nap.edu/read/4919/chapter/4