Glen Canyon Dam Adaptive Management Program Administrative History

The Glen Canyon Dam Adaptive Management Program (AMP) has been identified as a model for natural resource management. We challenge that assertion, citing the lack of progress toward a long-term management plan for the dam, sustained extra-programmatic conflict, and a downriver ecology that is still in jeopardy, despite over ten years of meetings and an expensive research program. We have examined the primary and secondary sources available on the AMP’s design and operation in light of best practices identified in the literature on adaptive management and collaborative decision-making. We have identified six shortcomings: (1) an inadequate approach to identifying stakeholders; (2) a failure to provide clear goals and involve stakeholders in establishing the operating procedures that guide the collaborative process; (3) inappropriate use of professional neutrals and a failure to cultivate consensus; (4) a failure to establish and follow clear joint fact-finding procedures; (5) a failure to produce functional written agreements; and (6) a failure to manage the AMP adaptively and cultivate long-term problem-solving capacity.

Adaptive management can be an effective approach for addressing complex ecosystem-related processes like the operation of the Glen Canyon Dam, particularly in the face of substantial complexity, uncertainty, and political contentiousness. However, the Glen Canyon Dam AMP shows that a stated commitment to collaboration and adaptive management is insufficient. Effective management of natural resources can only be realized through careful attention to the collaborative design and implementation of appropriate problem-solving and adaptive-management procedures. It also requires the development of an appropriate organizational infrastructure that promotes stakeholder dialogue and agency learning. Though the experimental Glen Canyon Dam AMP is far from a success of collaborative adaptive management, the lessons from its shortcomings can foster more effective collaborative adaptive management in the future by Congress, federal agencies, and local and state authorities.

Even unmanaged ecosystems are characterized by combinations of stability and instability and by unexpected shifts in behavior from both internal and external causes. That is even more true of ecosystems managed for the production of food or fiber. Data are sparse, knowledge of processes limited, and the act of management changes the system being managed. Surprise and change is inevitable. Here we review methods to develop, screen, and evaluate alternatives in a process where management itself becomes partner with the science by designing probes that produce updated understanding as well as eco- nomic product.

Renewable natural resources provide important contributions to food, fiber, and recreation in many parts of the world. The economies of some regions a r e heavily dependent on fisheries and forestry, and consumptive use of wildlife (hunting) is a traditional recreational pastime across Europe and North America. The management of renewable resources usually involves public agencies that are responsible for harvest regulation, and often production enhancement, so as to provide sustainable yields into the long-term future (resource husbandry). The track record of such agencies has been spotty: many resources have been mined to low levels before effective harvest regulation could be developed, while others have been managed so conservatively as to miss major harvesting opportunities.

Three key features of renewable resources have made them difficult to manage. First, sustainable production depends on leaving behind a "capital" stock after each harvesting, and there are definite limits to the production rates that this stock can maintain. Second, harvesting is normally undertaken by a community or industry of harvesters whose activities (investment, searching, etc.) are not completely monitored or regulated, so that dynamic responses, such as overcapitalization of fishing fleets, are common. Third, the biological relationships between managed stock size and production rates arises through a complex interplay between the organisms and their surrounding ecosystem; for any particular population, this relationship cannot be predicted in advance from ecological principles and must, instead, be learned through actual management experience.

This book is on the various methods of environmental impact assessment as a guide to design of new environmental development and management projects. This approach surveys the features of the environment likely to be affected by the developments under consideration, analyses the information collected, tries to predict the impact of these developments and lays down guidelines or rules for their management.

This book is concerned with practical problems, e.g. development in Canada, the management of fisheries, pest control, etc. It is devoted to a general understanding of environmental systems through methods that have worked in the real world with its many uncertainties. It does not reject the concept of environmental impact analysis but rather stresses the need for fundamental understanding of the structure and dynamics of ecosystems.