Reservoir Area of Influence and Implications for FisheriesManagement

Understanding the spatial area that a reservoir draws anglers from, defined as the reservoir’s area of influence, and the potential overlap of that area of influence between reservoirs is important for fishery managers. Our objective was to define the area of influence for reservoirs of the Salt Valley regional fishery in southeastern Nebraska using kernel density estimation. We used angler survey data obtained from in-person interviews at 17 reservoirs during 2009–2012. The area of influence, defined by the 95% kernel density, for reservoirs within the Salt Valley regional fishery varied, indicating that anglers use reservoirs differently across the regional fishery. Areas of influence reveal angler preferences in a regional context, indicating preferred reservoirs with a greater area of influence. Further, differences in areas of influences across time and among reservoirs can be used as an assessment following management changes on an individual reservoir or within a regional fishery. Kernel density estimation provided a clear method for creating spatial maps of areas of influence and provided a two-dimensional view of angler travel, as opposed to the traditional mean travel distance assessment. The research of motives and site-selection behavior is common in recreational fisheries (Jakus et al. 1997; Schramm et al. 2003; Hunt 2005; Sutton and Ditton 2005; Carlin et al. 2012; Aas and Onstad 2013; De Freitas et al. 2013). One important component highlighted in the research on site selection is the importance of travel distances (Arlinghaus and Mehner 2004). Travel distance is defined as the distance required for a participant to travel from their home to participate in the activity and is often used as a surrogate for travel cost or the cost to participate in the activity at that given location. One technique that may be used to analyze spatial data is kernel density estimation (Worton 1989; Seaman and Powell 1996). Kernel density estimation provides a clear method for creating spatial maps of areas of influence, providing a twodimensional view of angler travel as opposed to the traditional one-dimensional mean travel distance assessment. This technique has been used for many years to define the home ranges of study animals. Kernel density estimation has also been used in the business and social science fields to determine the best placement of new hospitals for distributing customer usage (Donthu and Rust 1989), determine the distribution of traffic accidents (Xie and Yan 2008), and determine the distribution of crime hot spots (Wang et al. 2013). However, kernel density estimation has not yet been widely applied to recreational fisheries (see Vokoun 2003 for an example of univariate kernel density home range analysis). Our objectives were to (1) describe the distributions of distance traveled, (2) compare travel distance between reservoirs and day-type, and (3) define the area of influence for each reservoir using kernel density estimation for the Salt Valley regional fishery in southeastern Nebraska. We used angler survey data obtained from in-person interviews conducted at these reservoirs to assess these three objectives.