My project is slowly beginning to come along. I was able to get a GIS layer of the town boundaries in Vermont that contains the harvest rates for each town for 2010, 2011, and 2012. I also have a WMU (wildlife management unit) boundary layer for the state of Vermont. This layer contains a column showing the number of hours hunters logged during the annual deer hunter survey to act as a proxy for overall hunter distribution/effort. Along with the GIS layers, I have the current deer population estimate (pre-hunt) by physiographic region and WMU and the sighting rates for each region/WMU and statewide from 2003-2012. Luckily, there is a very cooperative deer project leader working for Vermont Fish and Wildlife who is more than willing to give me any deer information I need for my project. From the information given to me, I have the hunting kill rates per WMU which comes from the success rates and the number of permits distributed. To explain the differences in kill rates and success rates between the WMUs is likely based on multiple environmental characteristics. These would be the same environmental factors that are influencing the differing deer populations in each WMU or town. These environmental factors include land cover (forest or not), proximity to edge, slope/elevation, proximity to deer wintering areas, and possibly distance to roads and rivers. I think this would make my model a type of multiple criteria evaluation. To account for these factors, I think I would need multiple calculate map functors with equations for each of these factors to determine the habitat suitability of each cell of an input landscape map of Vermont. Maybe I could get the output to be a categorical map with values from 0 to 5 ranking the habitat suitability of each cell based on the equations.
As for the deer population simulation without hunting, the biggest non-hunting factor impacting deer mortality is winter severity. This needs to be taken into consideration when trying to determine how the population will grow and spread without hunting pressure. In this case, it may be important to consider historical WSI recordings and the region specific regression equation that the deer project leader can provide. This is all the information I have so far on my project. It’s not much, but it’s definitely a start and it is slowly becoming less confusing and daunting.