Humans kill approximately 500 million to 1 billion

            Humanskill approximately 500 million to 1 billion birds a year through direct andindirect contact (Erickson et al.

2005).   Bird mortality associated with vehiclecollisions is just one example of a negative direct interaction between humansand birds, and it has been documented that a taxonomically diverse group ofbirds are susceptible to mortality from contact with vehicles (Case 1978,Decker 1987, Ashley and Robinson 1996). One particular family of birds, Anatidae, or commonly known aswaterfowl, are susceptible to these incidents when their habitat is in closeproximity to high traffic areas.  Liketheir name suggests, these birds primarily reside in areas with water, mostcommonly in wetlands.  Wetlands arehighly productive, and for waterfowl, are an important food resource, source ofnesting habitat, and habitat in general.

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 The prairiepothole region in the Central United States has extremely high numbers ofwaterfowl due to a high density of wetlands and small lakes.  These birds use this region as a migrationroute where they may stop to rest and replenish energy stores, as well as anesting area.  One study by Sargeant(1981) focused on mortality associated with vehicles in North and South Dakota,an area in the prairie pothole region, estimating mortality in this region dueto roads at 4,500 ducks per 4 months, or 13,500 per year (Sargeant 1981).  This prairie pothole region is a veryproductive region for the recruitment of waterfowl in the Central flyway, whencompared to another flyway, the Atlantic flyway.  However, the population of humans in thisregion is substantially lower than of another region, the Atlantic flyway.  The Atlantic flyway encompasses the EastCoast of the United States and is used by both sea ducks as well as land ducksand species of geese and swan.  With thisarea being high in human population and a main route for waterfowl, vehiclestrikes, while not studied, should be a high priority for research.  While this study could not approximate howmany waterfowl will be killed, it can be used to inform a specific area of oneway they can protect these waterfowl from being killed from vehicles.

  This area is of high interest as it islocated within 5 miles of the Delaware River, an important migratory route onthis flyway.  Also noteworthy is thisarea is subjected to high traffic from large vehicles due to a landfilloperated by Waste Management within this study region.  This landfill receives waste not only fromthe surrounding area, but also as far away as New York City, approximately 75miles away.  Problem:            Thisquestion will investigate areas deemed as high priority habitat for bothresident waterfowl and for those birds stopping along their migration route.  This area will then be related to how closeit is to roads to determine which areas of food are of high concern for vehiclestrikes.  Our analysis will attempt toanswer the following question:  Where are high priority waterfowl habitats,and what would be the associated cost of protecting these areas with fencing?Data and Approach:            Thefirst piece of data we used was an image of Tullytown from the data set NAIPGeotiff.  All it contains is an image ofthe area of interest.  The metadatais:  Vintage- 8/24/17, Resolution-1m, Coordinate System-WGS_1984_Web_Mercator_Auxiliary_Sphere, and Datum-NAD83.

  The next data we usedwas the NHD of Pennsylvania Shapefile. This data contains many various files, but the one we used was theNHDWaterbody which contained the necessary waterbodies we wanted to use.  The metadata is:  Vintage- 9/14/17, Resolution-1:24,000-scaledata, Coordinate System- GCS_North_American 1983, and Datum- NAD83.  The final data we used was the USGS NTD forthe roads layer.  This also contains manydifferent files, but we used the RoadSegment file for our analysis.

  The metadata is: Vintage- 8/19/17,Resolution-1:24,000-scale data, Coordinate System- GCS_North_American 1983, andDatum- NAD83.  We began our analysis byreprojecting everything into WGS_1984_Web_Mercator_Auxiliary_Sphere.  We then clipped both the NHD data and NTDdata to the extent of our image.  On ourhydrography data, we had to do a -10m buffer, 10MBufferInside, to get a lakewith 10m around the edge removed, and then we created a 10m buffer on the -10mbuffer layer to get the shoreline created, Shorelinebuffer.  What also was done before any other analysiswas that aquatic vegetation was digitized from the Tullytown image file.  In this digitization step, you could clearlysee water lilies as well as submerged aquatic vegetation, which were bothdigitized, creating a new shapefile called Food, and calculating area in squaremeters and hectares.  The roads layer wasalso buffered 100m, creating a new layer called RoadBuffer.

  Next came the critical intersects, beginningwith the food and shoreline layers, creating a layer that highlights where thefood is within 10m of the shoreline, Food_Shoreline_Intersect.  This layer was then intersected with the roadbuffered layer to get a high priority area close to the roads, calledHighFood_Intersect, again calculating area in square meters and hectares.  From this layer, we digitized a fence, unlessthe area was sticking into the water as an edge, because the birds could belimited in their food access.  This finallayer was known as the High Risk Fence, with us calculating length, in metersfor our cost analysis, in meters.  Wecreated another fence from our Food layer and our Road layer.  This layer was called Food_Road_Intersect,and we calculated area in square meters and hectares, creating a layer withfood close to roads, but not necessarily on the shoreline.  From this intersected layer, we againdigitized a fence, naming it Medium Risk Fence, again calculating length, inmeters, for our cost analysis, in meters.

Results:            Ourresults can be seen in Table 1, as well as our final map, where it highlightsthat there is a smaller area of food that is both near roads and shorelines,when compared compared to the food just near the roads.  We also provided a cost to two types offences, Medium Risk and High Risk, based on their location to both the Food nearthe Roads layers, or MediumFood_Intersect, and the HighFood_Intersect.  This data can be seen in Table 2, with theHigh Risk Fence being smaller and costing less, with the cost for both fencesbeing associated with the Critterfence 700 fence.Discussion:            Basedon our analysis of where waterfowl feed and their proximity to roads, we have providedthe town of Tullytown, and Waste Management, as they are the primary trafficissue, two fences that can be constructed to protect these waterfowl from beinghit by vehicles.  Due to the high volumeof traffic this area sees, we believe these fences, while birds may fly overthem, will help reduce mortality from vehicle strikes in these areas due to thenature of the birds not walking up the shoreline to rest.

  We also believe this model, or one similar toit, can be fitted to any other areas of interest in determining where wildlifecan be protected from vehicle strikes, whether it be waterfowl or otheranimals, using data on their optimal habitat. This analysis provides not only the locations, but also the costassociated with erecting these fences to protect the waterfowl, and thus givesthe town and company enough information to decide where these fences might beoptimally constructed.


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