Derek Kauneckis Associate Professor Dept. of Political Science University of Nevada, Reno Reno, Nevada 89557 kauneck@un

1. Assessing climate policy networks in Nevada water management Orion Cuffe, Ph.D.Student, Political Science Department, University of Nevada, Reno Derek Kauneckis, Associate Professor, Political Science Department, University of Nevada, Reno Orion Cuffe Ph.D. Student Dept. of Political Science University of Nevada, Reno Reno, Nevada 89557 orion.cuffe@gmail.com Derek Kauneckis Associate Professor Dept. of Political Science University of Nevada, Reno Reno, Nevada 89557 kauneck@unr.edu  Overview The basic science of climate change is well established. However, climate change science that is directly applicable to adaptation policy in critical areas like water management is emerging at a rapid pace. Research in evolving areas like local and regional impacts predictions ,climate model down-scaling, and land use effects are crucial to climate adaption planning (Cuffe and Kauneckis 2011). Water management is considered to be one of the most vulnerable sectors to the effects of climate change , especially in arid states like Nevada. Policy networks have been shown to be effective at increasing the sharing of knowledge between organizations, facilitating the coordination of activities, and building trust and reciprocityamong policymakers and stakeholders(Agranoff 2007, Schneider et. al. 2003, Scholz et. al 2008). For those reasons, policy networks will likely be a necessary component in the adaptation of water management and infrastructure to the predicted effects of climate change Major impediments to fully leveraging the power of networks include the difficulty of creating new networks, expanding existing ones in order to include relevant actors and stakeholders, and improving communication gaps and bottlenecks (Considine 2009, Prell et. al. 2009). This study applies social network analysis techniques to examine existing climate policy networks among water management organizations at the state and local levels in the State of Nevada. Through this analysis we seek to uncover new opportunities to increase collaboration between organizations in order to bring about more effective adaptation policy responses to climate change. Business Results Figure 2: Existing Climate Policy Network in Nevada Water Management Existing Network Density: 0.20 Organizations with no ties in existing network: Methodology In order to measure the existing policy network among water management agencies, data was collected from the Nevada Climate Change Survey of Public Organizations (Cuffe and Kauneckis 2011). The population surveyed was composed of representatives of all public agencies and non-governmental organizations that could be indentified in Nevada whose activities include natural resource or environmental management. A total of 204 invitations were extended and there were 60 surveys completed, for a response rate of 29.4%. Respondents answered open-ended questions that prompted identifying those organizations with whom they regularly meet to discuss issues related to climate change planning. Respondents were similarly asked to identify those organizations who they felt were important to include in state-level climate change planning efforts. Only those organizations that identified themselves as closely associated with water resourceswere included in the social network analysis presented here. Each respondent organization was coded into one of six organizational categories. Those organizations that were identified by the respondents were coded into one of eleven categories. Ties between the categories were identified through a binary analysis using the social network analysis software UCINET. Figure 1: Types of organization included in the study Figure 3: Improved Network That Includes all Organizations Identified as Being Important to Climate Change Policy Improved Network Density: 0.45 . Discussion Figure 2 represents the existing policy network. The self-identified groups of respondents (red circles) identified the organizations with which they are currently working on issues specifically related to climate change planning (blue squares) . Figure 3 represents the policy network that would emerge if all of the groups identified as being important to climate change policy were included. The measure of the density of a network describes the percentage of all possible ties that are present in the relational matrix. The density differentialbetween the two networks (0.26) suggests a significant opportunity to increase the structure of the policy network. Revealed deficiencies in the existing network include the lack of connections in policymaking to the business community, Native American governments, and higher education research. In particular, the centrality of regional and state agencies in Figure 3 suggests that their lack of involvement in the existing policy network indicates existing gaps and bottlenecks. Sources Cited Agranoff, Robert (2007) Managing Within Networks. Washington, DC: Georgetown University Press. Considine, Mark, Jenny M. Lewis and Damon Alexander (2009) Networks, Innovation and Public Policy. New York: Palgrave Macmillan. Cuffe, Orion and Derek Kauneckis (2011) “Nevada Climate Change Survey of Public Organizations: Executive Summary.” Prell, C., K. Hubacek, et al. (2009). "Stakeholder analysis and social network analysis in natural resource management." Society & Natural Resources 22: 501-518. Schneider, Mark, John Scholz, Mark Lubell, DenisaMindruta and Matthew Edwardsen (2003) “Building Consensual Institutions: Networks and the National Estuary Program.”American Journal of Political Science 47 (1): 143-158. Scholz, J., R. Berardo, et al. (2008). "Do networks solve collective action problems? Credibility, search, and collaboration." The Journal of Politics 70(02): 393-406. . . Special thanks to the Nevada Experimental Program to Stimulate Competitive Research (EPSCoR) at the National Science Foundation (NSF) for financial support of this research.