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This brief article, written for a symposium on "Collaboration and the Colorado River," evaluates the U.S. Department of the Interior's Glen Canyon Dam Adaptive Management Program ("AMP"). The AMP has been advanced as a pioneering collaborative and adaptive approach for both decreasing scientific uncertainty in support of regulatory decision-making and

This brief article, written for a symposium on "Collaboration and the Colorado River," evaluates the U.S. Department of the Interior's Glen Canyon Dam Adaptive Management Program ("AMP"). The AMP has been advanced as a pioneering collaborative and adaptive approach for both decreasing scientific uncertainty in support of regulatory decision-making and helping manage contentious resource disputes -- in this case, the increasingly thorny conflict over the Colorado River's finite natural resources. Though encouraging in some respects, the AMP serves as a valuable illustration of the flaws of existing regulatory processes purporting to incorporate collaboration and regulatory adaptation into the decision-making process. Born in the shadow of the law and improvised with too little thought as to its structure, the AMP demonstrates the need to attend to the design of the regulatory process and integrate mechanisms that compel systematic program evaluation and adaptation. As such, the AMP provides vital information on how future collaborative experiments might be modified to enhance their prospects of success.

ContributorsCamacho, Alejandro E. (Author)
Created2008-09-19
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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

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.

ContributorsSusskind, Lawrence (Author) / Camacho, Alejandro E. (Author) / Schenk, Todd (Author)
Created2010-03-23
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DescriptionUnderstanding the evolution of opinions is a delicate task as the dynamics of how one changes their opinion based on their interactions with others are unclear.
ContributorsWeber, Dylan (Author) / Motsch, Sebastien (Thesis advisor) / Lanchier, Nicolas (Committee member) / Platte, Rodrigo (Committee member) / Armbruster, Dieter (Committee member) / Fricks, John (Committee member) / Arizona State University (Publisher)
Created2021
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This dissertation consists of three papers about opinion dynamics. The first paper is in collaboration with Prof. Lanchier while the other two papers are individual works. Two models are introduced and studied analytically: the Deffuant model and the Hegselmann-Krause~(HK) model. The main difference between the two models is that the

This dissertation consists of three papers about opinion dynamics. The first paper is in collaboration with Prof. Lanchier while the other two papers are individual works. Two models are introduced and studied analytically: the Deffuant model and the Hegselmann-Krause~(HK) model. The main difference between the two models is that the Deffuant dynamics consists of pairwise interactions whereas the HK dynamics consists of group interactions. Translated into graph, each vertex stands for an agent in both models. In the Deffuant model, two graphs are combined: the social graph and the opinion graph. The social graph is assumed to be a general finite connected graph where each edge is interpreted as a social link, such as a friendship relationship, between two agents. At each time step, two social neighbors are randomly selected and interact if and only if their opinion distance does not exceed some confidence threshold, which results in the neighbors' opinions getting closer to each other. The main result about the Deffuant model is the derivation of a positive lower bound for the probability of consensus that is independent of the size and topology of the social graph but depends on the confidence threshold, the choice of the opinion space and the initial distribution. For the HK model, agent~$i$ updates its opinion~$x_i$ by taking the average opinion of its neighbors, defined as the set of agents with opinion at most~$\epsilon$ apart from~$x_i$. Here,~$\epsilon > 0$ is a confidence threshold. There are two types of HK models: the synchronous and the asynchronous HK models. In the former, all the agents update their opinion simultaneously at each time step, whereas in the latter, only one agent is selected uniformly at random to update its opinion at each time step. The mixed model is a variant of the HK model in which each agent can choose its degree of stubbornness and mix its opinion with the average opinion of its neighbors. The main results of this dissertation about HK models show conditions under which the asymptotic stability holds or a consensus can be achieved, and give a positive lower bound for the probability of consensus and, in the one-dimensional case, an upper bound for the probability of consensus. I demonstrate the bounds for the probability of consensus on a unit cube and a unit interval.
ContributorsLi, Hsin-Lun (Author) / Lanchier, Nicolas (Thesis advisor) / Camacho, Erika (Committee member) / Czygrinow, Andrzej (Committee member) / Fishel, Susanna (Committee member) / Motsch, Sebastien (Committee member) / Arizona State University (Publisher)
Created2021