What Roadkills Did We Miss in a Driving Survey? A Comparison of Driving and Walking Surveys in Baldwin County, Georgia

Accurate estimates of vertebrate road mortalities are necessary prior to the consideration of mitigation measures by resource managers. Due to ease of implementation, driving surveys are more common than walking surveys. From February 2018 to February 2019, two survey methods, driving and walking, were used to monitor a 1.16 km section of Highway 212 in Baldwin County, Georgia. Roadkills were identified and monitored for persistence from sunrise to noon two days a week. Twenty-nine roadkills were recorded over the survey period: 48.3% mammals (14/29), 27.6% herpetofauna (8/29), and 24.1% birds (7/29). Forty-eight percent (14/29) of roadkills were missed by the vehicle survey: 75.0% of herpetofauna, 43.9% of birds, and 35.7% of mammals. Of the roadkills missed, 72.7% (8/14) were located in the roadway compared to the verge. Carcasses smaller than eastern gray squirrel size were more likely missed in the driving survey than those equal to or larger than squirrels (c2=4.36; p=0.04). This study demonstrates that driving surveys miss a significant portion of roadkills and conducting walking surveys separately or in combination with driving surveys is necessary for an accurate estimate of vertebrate road mortality

Identifying Roadkill Hotspots Using a Running Average

The identification of roadkill hotspots is necessary prior to the consideration of wildlife road mortality mitigation measures. In a previous study, 178 roadkill specimens were tallied via a driving survey along 21.4 km (13.3 mi) on three connected roadways in Baldwin County, Georgia. Roadkill locations were recorded to the nearest 0.16 km (0.1 mi) using the vehicle odometer. In the current study, location data were used to generate three graphical displays of roadkill distribution: 1) a linear graph of roadkills per 0.16 km (0.1 mi) bin; 2) a linear graph of roadkills per 0.8 km (0.5 mi) bin; and 3) a linear graph with a continuous running average incorporating 0.48 km (0.3 mi). The number and position of the peaks on each graph were compared in relation to roadway features that may influence animal movement and mortality such as vegetative boundaries, stream crossings, hills, and curves. The running average plot provided the best visual illustration of roadkill hotspot locations in relation to roadside features. The running average is a good technique to quickly and accurately identify hotspot locations and could help resource managers plan mitigation strategies to decrease wildlife road mortality