Natural Disturbance Production Functions

Natural disturbances in forests are driven by physical and biological processes. Large, landscape scale disturbances derive primarily from weather (droughts, winds, ice storms, and floods), geophysical activities (earthquakes, volcanic eruptions, even asteroid strikes), fires, insects, and diseases. Humans have always been affected by these processes and have invented ways to harness such processes or manipulate vegetation to enhance the values obtained from nature or reduce their negative impacts on human societies. For example, humans have cleared brush using fire to reduce pest populations and encourage forage for animals (Pyne 1995). Historically, humans have relied on traditions, rules of thumb, and trial and error to predict how their actions may affect disturbance probabilities and characteristics. More recently, economic assessment tools have helped gauge the consequences of natural disturbances on forests.

As the availability of science, technology, and environmental data have improved, scientists and economists have been able to quantify disturbances as production processes that emanate from a combination of biological, physical, and (or) human-initiated inputs. Ecologists have long recognized that disturbances lead to changes in ecological communities, which subsequently affect human societies. Economists, on the other hand, have been focused on understanding how humans can intervene to alter both the frequency and severity of natural disturbances. Improving scientific and economic assessment tools, and experience using them, have in turn helped us to appreciate the many consequences of natural disturbances. The objectives of this chapter are to (1) define disturbances and their stages, (2) discuss how mathematical expressions of disturbance processes, disturbance production functions, may differ from the production functions defined in neoclassical economics, (3) identify the stages of disturbances, (4) provide a typology of production functions relevant to forest disturbances, and (5) conclude with a discussion of management and science implications of recent research. Our focus is to understand how disturbances are produced and how they may be affected by intentional managerial actions. We show that quantitative characterization of disturbance processes is required to understand how management interventions into disturbances can lead to net societal gains. Throughout the chapter, we provide examples of how information about disturbances can be used to better achieve management and policy goals.