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Ecosystem Management

Chad Oliver
Yale university

Ecosystem management uses the concept of “systems” to achieve the desired and possible values from forests. It involves several steps: understanding the forest being managed; making the objectives of management explicit; and developing ways to modify the forest to achieve the objectives as much as possible. In the late 1800’s management was recognized as a science in which different approaches could be tested for effectiveness in achieving goals (Wilson 1887, Taylor 1911); and systems concepts were used as a way of dealing with otherwise overwhelming complexity. These concepts had unconsciously been used by people for millennia; however, they have only been made conscious and explicit during the past 200 years.

Systems concepts also began being incorporated into scientific research in the late 1800’s. The term “ecosystem” was proposed by Tansley in 1935 as a way of studying ecology using these concepts; “ecosystem management” was used as a term by Agee and Johnson in 1987. Systems concepts can be transportable to different spatial scales, and ecosystems can be as small as the microbes in a Petri dish to as large as the Earth (Kimmins 1987).

Systems concepts simplify thinking, analyses, and management by combining many entities into groups; naming the groups; and addressing the major interactions within and between the groups (Cleland and King 1968, Blau and Schoenherr 1971). These groups are variously referred to as “systems,” “components,” ”locations,” “stations,” or other discipline-specific names. The delineation, or bounding, of a system can be arbitrary and depends on the objectives of the study. A system, can be as small as a single atom, when subatomic particles are studied within the system or when the interaction among atoms are used to study molecules. Ecosystems generally examine interactions among multiple organisms and their environment.

Once a system is delineated, groups within it are referred to subsystems or subcomponents. A system or subsystem can be characterized in many ways. The measurable conditions of the important characteristics of a system or subsystem at a given time are referred to as “events,” “patterns,” or “structures.” They are often the amalgamations or “emergent properties”of many measures. For example, a tree’s diameter is actually the emergent property of the size of many individual cells. A stand’s “structure” (e.g., “old growth” or “savanna”) is also an emergent property.

A system can have interactions with other systems outside of its bounds; a.k.a., “activities,” “processes,” and “functions,” referred to as “external” interactions. Similar “internal” interactions occur among subsystems within the bounds of a system. Management and research can concentrate on external or internal interactions or both. Where a watershed is delineated as a system, individual stands can be subsystems, and other adjacent watersheds can be other systems. A hurricane impacting one or more stands in the watershed would be considered an external interaction; whereas growth and death from competition would be considered internal.

Many external and internal interactions can occur among systems or subsystems and influence different properties of a system. To avoid complexity, interactions perceived to be unimportant are ignored. The interactions that are considered important, and therefore analyzed, are commonly amalgamations or emergent properties—similar to the measurable conditions of a system. For example, a fire that spreads from one stand to another is an interaction, but is actually an emergent property of more complex chemical reactions.

Ecosystem management necessarily includes people as part of ecosystems, since the values to be managed for are people-centered. Studies of ecosystems in the biological sciences sometimes delineate ecosystems so that human actions are external influences. For example, ecosystem management may consider a village or city within the watershed as part of the ecosystem, whereas ecological research may exclude it to concentrate on non-anthropogenic influences. Where people are considered an internal influence on the ecosystem, a controlled fire that increases the amount of savanna structure for animal habitat would be an internal influence.

The interactions that influence a system or subsystem are referred to as “inputs,” and the influences that come from a system or subsystem and are exerted on others are referred to as “outputs.” For example, the input of growth on some species and soil conditions can create overcrowding and result as insect outbreaks that travel to other stands as an output. A second input to the crowding stand could be a thinning harvest, which reduces or avoids the insect output and creates an output of timber from the harvested trees; however, an incorrectly done thinning could create silt in a stream and thus influence other conditions and outputs of the system. Much of correctly characterizing a system is based on understanding the relation of these inputs and outputs. The ability to understand, and therefore predict, the relation of these inputs to outputs defines the robustness of the delineation of the systems, subsystems, and interactions.

Systems that produce a given output or receive the input from another system (external interactions) are referred to as “open” relative to that interaction; “closed” systems are those with no net input or output of a given form from another system. “Stable” systems are ones that do not change the properties being measured over time, as opposed to “dynamic” systems that do change these properties. “Static” systems do not change their output being measured over time, as opposed to “variable” systems whose output does change.

Depending on what conditions or interactions are measured, systems can simultaneously be stable, dynamic, closed, and open at any time. For example, a stand in a forest could be closed relative to phosphorus if no phosphorus is leached out of the stand. The same forest system could be open relative to migratory birds that move between that forest and another one thousands of miles away. Until the 1980’s, a forest ecosystem in which people were excluded was considered both stable and static; documentation of windstorms, volcanic eruptions and other natural, external inputs showed otherwise.

The grouping into systems, ignoring of unimportant interactions, and use of emergent properties necessitates decisions. The decisions are put forth as scientific hypotheses, which are tested both by determining the internal consistency and logic of the hypothesis and by determining if the output and changed nature of a system can be predicted by the hypothesis. These hypotheses are also known as scientific theories, scientific laws, or paradigms.

These hypotheses can change with time and are referred to as “paradigm shifts” (Kuhn 1970). Acceptance of a new paradigm usually takes time, during which confusion occurs because different people are embracing different paradigms. Most paradigms accurately predict some outputs but not others. Paradigms are constantly being adjusted in small and large ways as management or research reveals their inaccuracies. Systems—and ecosystems—approaches do not guarantee a correct answer; they simple form an organizational framework for avoiding becoming overwhelmed by complexity when trying to study or manage complex entities. Our paradigm of forest ecosystems has changed during the past few decades from assuming forests are largely closed, stable, static system unless people disrupt them to realizing that they are largely open, dynamic, and variable systems (Botkin 1990, Oliver and Larson 1996).

Ecosystem management seeks ways that an ecosystem can provides certain desired outputs or conditions at certain times, generally by influencing the type or amount of input. A general, but not universal, objective is to make appropriate changes in inputs into the system at times that will lead to the greatest provision of desired outputs—or the fewest undesirable ones. This gaining efficiency of inputs to outputs is referred to as “leveraging” the system.

Ecosystem management is an ongoing process, during which the ecosystem may change, the accepted scientific paradigm of how it behaves may alter, and the desired outputs people want may change. With prosperity, people have been demanding many outputs—a.k.a., values or management objectives--from ecosystems that formerly were ignored as “economic externalities.” For example, providing habitats for all species and avoiding siltation of rivers and streams were not considered valuable when people were desperate for jobs and timber; however, they are now considered values to be managed for.

Management must determine ways to gain leverage by altering the system and/or subsystem inputs to provide the desired outputs. Since forest ecosystems have many desired outputs, it is generally not possible to provide the maximum amount of all outputs at all times from each ecosystem. There may need to be tradeoffs among values; and there is a conceptual “response surface” among values. This response surface is a multidimensional surface with each dimension (or axis) representing one management objective. The surface shows the maximum amount of each other value that can be provided when a given amount of any single value is provided. Management attempts to manage on the response surface to ensure a minimum of negative tradeoffs among values is being made. Determining the exact shape of the response surface is nearly impossible because of the many objectives and the many ways an ecosystem’s inputs can be changed to affect the values. Computer models and other methods have been developed to help determine the conceptual response surface.

In previous decades, the now outdated paradigm assumed the forest was in a “steady state” or “climax” forest and essentially a closed system. Consequently, there was antagonism between providing presumed “natural” forest values such as habitats and providing more human-centric values such as fire protection and timber. I.e.,the response surface showed one set of values declined dramatically with any increase in the other set. The currently more accepted, dynamic perspective of forest ecosystems shows these values are more compatible and even synergistic, such that some increase in appropriate human activity and production of human-centric values can actually increase the amount of most “natural” values.

After the tradeoff among values, and hence the management approach, is decided upon (Oliver and Twery 1999), ecosystem management entails implementing the management plan—altering the appropriate inputs at the appropriate time and place to obtain the desired outputs. As in all complex systems, the targeted outputs and conditions are not perfectly achieved because of the necessary grouping involved in delineating the system, the ignoring of seemingly unimportant interactions, and the imperfect knowledge of all aspects of the system. Techniques such as Continuous Quality Improvement and Adaptive Management have been developed to allow feedback and correction of major discrepancies between the projected consequences of managing the system and the actual management. This correction can entail changes in management practices and/or changes in the scientific paradigm of the ecosystem.

Literature Cited

Kimmins, J.P. 1987. Forest Ecology. Macmillan Publishing Company, New York, 531 pp.

Wilson, W. 1887. The study of administration. Political Science Quarterly 2.

Taylor, F.W. 1911. The principles of scientific management. Harper and Brothers, New York.

Tansley, A.G. 1935. The use and abuse of vegetational concepts and terms. Ecology 16, 284-307.

Cleland, D.I. and W.R. King. 1968. Systems analysis and project management. McGraw-Hill, Inc. New York. 315 pp.

Blau, P.M., and R.A. Schoenherr. 1971. The structure of organizations. Basic Books, Inc. New York. 445 pp.

Kuhn, T.S. 1970. The structure of scientific revolutions. University of Chicago Press, Chicago. 210 pp.

Botkin, D.B. 1990. Discordant harmonies: a new ecology for the twenty-first century. Oxford University Press. New York. 241 pp.

Oliver, C.D., and B.C.Larson. 1996. Forest Stand Dynamics. Update edition. John Wiley & Sons. New York. 520 pp.

Oliver, C.D., and Mark Twery. 1999. Decision support systems/models and analyses. In Ecological Stewardship: A Common Reference for Ecosystem Management. Elsevier Science Ltd. Pp. 661-685.

Agee, J.K., and D.R. Johnson. 1987. Ecosystem management for parks and wilderness. University of Washington Press, Seattle.

Version #1; 15 May 2005

Posted 3 August 2006

Updated: 23 August 2007