On the Poverty of Theory: The Case of the Unknown Unknowns
Ulanowicz et al. 2009. Quantifying sustainability: Resilience, efficiency and the return of information theory. Ecological Complexity 6: 27-36
“The ecological analyst faces a dilemma: one the one hand, if any of their recommendations are to be followed, they must first recommend whatever will give the system a positive budget of flexibility… They must create flexibility and prevent the civilization from immediately expanding into it. It follows that the ecologist’s goal is to increase flexibility…” (Bateson, 1970)
“As we know, there are known knowns. There are things we know we know. We also know there are known unknowns. That is to say we know there are some things we do not know. But there are also unknown unknowns, the ones we don't know we don't know.” (Rumsfeld, 2006)
The non-linear turn in ecosystem dynamics has exposed large uncertainties in basic theory. Theories of alternative states, thresholds, recovery, and resilience are now confronted with questions that appear only tautologically answerable. For example, “what constraints are likely to be irreversible?” Yet, these questions arise only from the set of concepts, assumptions, and variables that are known about a particular (eco)system. But what about the things we don’t know we don’t know about? How do unknown unknowns contribute to the resilience and stability of an ecosystem? Ulanowicz et al. (2009) address this question in a 2009 paper. Following the late Bateson, a forefather of modern resilience theory, this paper argues that the interplay between presence and absence [of a system property or process] plays a crucial role in whether a (eco)system survives or disappears.” Using insights from IT theory, they suggest that the absence of order (i.e (bio)diversity), together with reserve capacities, provides (eco)system stability over the long run. They concluded by suggesting that there must be theoretical distancing from ecological theories that emphasize efficiency. Yet even in a case with unknown unknowns addressed, the question of uncertainly still remains.
How can we make ecological uncertainty legible, and in a way that makes it translatable to policy makers? Is it even possible?