Adaptive (Ecosystem) Management (LP&M #2)

The theory/practice dialectic strikes again. In our second four hour class, we spoke of a need for better management throughout all aspects of professional practice. The most relative precedent for this exists and is known as Adaptive Management (AM), or Adaptive Resource Management. Adaptive Ecosystem Management is the term used by our guest lecturer, ecologist Dr. Glenn Brown.

Regarding how the natural world has historically been “managed” there is only room for improvement. To date, we have yet to break from from a Newtonian Mechanics mode of thought regarding our relationship with natural resources and systems. Nature is not a mechanical system. As the findings from Buzz Holling, the founder of AM and the systems theory of Panarchy, have taught us, nature is a complex adaptive system. With such systems, the relationships between its parts are nonlinear, often nested, and have unknown thresholds. Any forces acting upon such systems can interrupt a system we have grown accustomed to and throw it into a new paradigm altogether. A common example used to explain this phenomenon is the North Atlantic Cod fisheries crash of 1992.

The primary difference between management practices of old and those of the Adaptive model is simple. AM requires constant modeling and checks of questions and assumptions. Because nature is dynamic and a complex adaptive system, and because we are of that system and not separate from it, we cannot apply mechanical thinking to it. When we do, fisheries can crash. When we do, recessions, like the one the globe has been experiencing since 2008, can hit hard. Yes, economies are complex adaptive systems as well.

Professional practice makes its profit from standardization. AM aims to account for the inevitable variabilities that arise with complex adaptive systems and recognize gaps in knowledge before they irreversibly impact the system. For professional practice to adopt AM as its management model, projects will require increases in funding. Standardization will be limited with any projects working directly with complex adaptive systems such as environment or economy. Approaches cannot remain the same from project to project. Furthermore, with AM, approaches should expect to shift several times within singular projects. Humans are capable of this approach. However, the elephant in the room–the bottom line–currently keeps tightening its belt.