The kernel density estimation revealed notable changes in the spatial distribution of the elk over time. In 2001, the highest density of elk was in Beaver Meadows and Fish Creek (with a peak density estimated to be 2600 elk! This estimate is much higher than the ecosystem of the park can withstand. In 2006 the elk have their peak density located in Moraine Park. There is still some concentration of elk in Beaver Meadows but the number of elk per square kilometer is much lower in 2006 then in 2001. Fish Creek continues to have the highest density of elk within the town. 2011 shows a dramatic increase in the density of elk overall, with the spatial distribution of elk still dominated by the areas of Moraine Park and Fish Creek. It is notable that the elk are more widely dispersed in other areas of the town of Estes Park. This could be an artifact of the high abundance and elk searching for alternative food sources.

The extremely high abundance of elk during the 2010-2011 bio-year lead the National Park Service to cull the population. We did not calculate the density of elk during years since this culling, but a future analysis of this data will definitely include this component.

The results of the statistical analysis suggest that development does have a marginally statistically significant negative effect on elk. As the percent of development increases, there is a multiplicative decrease in the number of elk by 0.16. This is a dramatic effect. With the ever expanding population of the front range of Colorado, there may be increases in the permanent development of Estes Park. Knowing that development does negatively reduce the elk population size in certain areas could help city planners to limit urban expansion. Maintaining a high density of the human population within the city may help the elk population by conserving wild habitat.

In this analysis we considered development to be either present or absent. Wild elk generally dislike human presence and avoid conflict with people. This particular herd do not have any predators (such as wolves) besides humans, so their behavior towards people has been documented to be more tolerant (Thompson, 1998). There are even cases when elk are attracted by human development, particularly when it is beneficial for elk browsing. For example, elk in this region have been observed to browse alfalfa fields along the front-range. They also are frequently observed to aggregate on the well-kept and watered golf course in Estes Park (located in the Fish Creek transect area). Further analysis could assess the influence of different kinds of development on the population size of elk and may reveal that more open agricultural development could actually increase the density.

There are several notable problems with the statistical analysis. First, the data were summarized over each of the years by taking the maximum elk count for each transect. By doing this data reduction, we were able to join the data more simply within ArcGIS with the development and transect data. However, taking this step was throwing out useful data. There would be more power for fitting the generalized linear mixed model if we did not reduce the data because we do actually have repeated measures within years and within transects. Reconstructing the data in excel is the obvious next step for this analysis.

A second issue with the statistical model is that all of the development, including the exclosures were lumped into a single year. A better approach would be to obtain development data at a finer time scale so that the effects of the exclosures that have been continuously built between 2008 through the present time would be examined. Additionally, we do have elk count data for years in which we do not have development data.

Another adjustment to this analysis that could help to properly infer the density estimation would be to use data in continuous space rather than in discrete space. We used the discrete space because the data we currently have access to were recorded in that way. We know there are specific location data available during elk counts from both aerial surveys and from ground counters. Once we obtain that data, a kernal density estimation procedure may be more accurate.

In conclusion, this analysis revealed support for the notion that development negatively impacts the abundance elk and influences the spatial distribution. Ungulate management on a national scale is a major issue for many wildlife areas which border urban and suburban development. Conflicts between ungulates and people are likely to increase as human development increase. The impact of development due to effects of habitat reduction and fragmentation are well known in many ecosystems and are no exception here (Vitousek, 1997).