Simulations. For P. molurus movement simulations, each individual was assigned a random home range center within 7 km (A = 14 km) of a linear road bisecting a uniform landscape. This landscape size was selected to ensure that the model had a high likelihood of simulating all snakes with a chance to cross the road; using A = 14 km, snakes had a less than 0.005% chance of crossing a road from that distance if the snake moved directly toward the road. Each time step was considered two days, and each simulation was run for 31 steps. We calculated the proportion of snakes that crossed the road on the 31st time step of the simulation to estimate probability over each two day step, and then divided by 18 h (assuming all road crossing activity occurs within an 9 h period each night) to calculate hourly individual road crossing probability (ρ). We simulated the movement of snakes under different movement scenarios. For each replicate simulation, we specified the following movement parameters: mean vector length (parameter defining turning angle distribution), strength of bias in response to road or home range center, and mean step size. Mean step size was a measure of the net distance a snake moved per day on average; this was parameterized using only daily relocations from the radiotelemetry data. The radiotelemetric data in our case study included limited numbers of road crossings, and thus we were unable to precisely parameterize the road bias component of our model. We therefore simulated a range of possible values for road bias, including both road avoidance and road attraction, and explored the sensitivity of our model output to assumptions about road behavior. The road bias parameter as defined in our model ranged from ‐0.3 to .3. A road bias value of 0 indicated that the snake biased its movement toward the home range center and displayed no behavioral response to the road. We considered this scenario our ‘null’ road bias scenario. A road bias value of 0.1 indicated that the snake biased its movement 10% toward the road and 90% toward the home range center. Similarly, a road bias value of ‐0.1 indicated that the snake biased its movement 10% away from the road and 90% toward the home range center. The mean vector length was a measure of the straightness of a snake’s movement path – a mean vector length of 0 indicates a fully random walk and a mean vector length of 1 indicates a completely straight movement path (100% probability of turning 0 degrees). We explored the sensitivity of the model to road bias and mean step size. We simulated a set of plausible values for each of these parameters, including three levels of road bias toward or away from a road (‐0.3, ‐0.1, 0, 0.1, 0.3), and three levels of mean step size based on telemetry data (upper and lower 95% confidence intervals (CI and mean step size). We simulated 7,000 snakes in each treatment combination and calculated the percentage of 7,000 snakes that crossed a road as a measure of daily road crossing probability. Results We successfully timed 31 wild P. molurus encountered naturally crossing roads at night in ENP (Table 4), that did not exhibit behaviors indicating that they had been disturbed (prolonged freezing, turning, or movement via lateral undulation). These individuals represented a variety of snake sizes (62 – 283 cm total length) and both sexes. Crawling speed varied considerably among individuals (range = 0.9 – 7.9 cm/sec; mean = 3.3 cm/sec; Table 4). Extrapolated to an average road width of 667 cm and considering that a snake must also crawl its own body length to leave the road, we estimated that a snake would be detectable on the road (total crossing time) for an average of 5.28 min (Vsnake = 5.28; 95% CI = 4.27 – 6.29 min). There was a positive correlation between snake length and crawling speed (linear regression; p = 0.04; R2 = 0.13), but the low R2 indicates that length accounts for little of the variation in speed. Moreover, there was not a significant relationship between snake length and total crossing time (p = 0.21; R2 = 0.05). Thus, larger pythons crawled more quickly, but because they had to crawl a longer distance to get off the road, total crossing time was similar across snake sizes.
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Simulations. For P. molurus simus movement simulations, each individual was assigned a random home range center within 7 km 500 m (A = 14 1 km) of a linear road bisecting a uniform landscape. This landscape size was selected to ensure that the model had a high likelihood of simulating all snakes with a chance to cross the road; using A = 14 1 km, snakes had a less than 0.005% chance of crossing a road from that distance if the snake moved directly toward the road. Each time step was considered two daysone day, and each simulation was run for 31 stepsdays. We calculated the proportion of snakes that crossed the road on the 31st time step of the simulation to estimate probability over each two day stepdaily road crossing probability, and then divided by 18 8 h (assuming all road crossing activity occurs within an between 9 h period each nightam and 5 pm) to calculate hourly individual road crossing probability (ρ). We simulated the movement of snakes under different movement scenarios. For each replicate simulation, we specified the following movement parameters: mean vector length (parameter defining turning angle distribution), strength of bias in response to road or home range center, and mean step size. Mean step size was a measure of the net distance a snake moved per day on average; this was parameterized using only daily relocations from the radiotelemetry data. The radiotelemetric data in our case study included limited numbers of road crossings, and thus we were unable to precisely parameterize the road bias component of our model. We therefore simulated a range of possible values for road bias, including both road avoidance and road attraction, and explored the sensitivity of our model output to assumptions about road behavior. The road bias parameter as defined in our model ranged from ‐0.3 ‐1 to .31. A road bias value of 0 indicated that the snake biased its movement toward the home range center and displayed no behavioral response to the road. We considered this scenario our ‘null’ road bias scenario. A road bias value of 0.1 indicated that the snake biased its movement 10% toward the road and 90% toward the home range center. Similarly, a road bias value of ‐0.1 indicated that the snake biased its movement 10% away from the road and 90% toward the home range centercenter (Examples of movement paths: Fig 3). The mean vector length was a measure of the straightness of a snake’s movement path – a mean vector length of 0 indicates a fully random walk and a mean vector length of 1 indicates a completely straight movement path (100% probability of turning 0 degrees). We explored the sensitivity of the model to road bias bias, turning angle distribution, and mean step size. We simulated a factorial set of plausible values for each of these parameters, including three levels of mean vector length (0.5, 0.7, and 0.9), five levels of road bias toward or away from a road (‐0.3, ‐0.1, 0, 0.1, 0.3), and three five levels of mean step size based on telemetry data (upper and lower range of step sizes, upper 95% confidence intervals (CI) and lower 95% CI of step sizes, and mean step size). Therefore, we simulated a total of 75 combinations of snake movement values. We simulated 7,000 35,000 snakes in each treatment combination and calculated the percentage of 7,000 35,000 snakes that crossed a road as a measure of daily road crossing probability. Results We successfully timed 31 nine wild P. molurus H. simus encountered naturally crossing roads at night in ENP (Table 42), that did not exhibit behaviors indicating that they had been disturbed (prolonged freezing, turning, or movement via lateral undulation). These individuals represented a variety of snake sizes and included animals crossing both paved and unpaved (62 – 283 cm total lengthsand) and both sexesroads. Crawling Crossing speed varied considerably among individuals (range = 0.9 0.6 – 7.9 2.9 cm/sec; mean = 3.3 1.5 cm/sec; Table 42), with no clear pattern relating to road type or snake size. Extrapolated to an average road width of 667 cm and considering that a snake must also crawl its own body length to leave the road550 cm, we estimated that a snake would be detectable on the road (total crossing time) for take an average of 5.28 7.69 min (Vsnake = 5.28; 95% CI = 4.27 5.42 – 6.29 9.96 min) to completely cross a typical road (Vsnake = 7.69). There was a positive correlation between Our crossing speeds were nearly identical to those of congeneric H. platirhinos measured in another study of snake length road crossing behavior (▇▇▇▇▇▇▇ and crawling speed ▇▇▇▇▇▇▇ 2005). A total of 656 h of systematic fall road surveys over 9 years in the North Carolina Sandhills yielded 54 captures of live H. simus (linear regression; p Table 1) and mean capture rate of 0.082 live snakes per hour of survey (Nobs = 0.04; R2 = 0.130.082). Capture rates varied considerably among years (Table 1), but the low R2 indicates that length accounts for little calculating an annual grand average across years yields a nearly identical capture rate of the variation in speed. Moreover, there was not a significant relationship between snake length and total crossing time 0.083 (p SD = 0.21; R2 = 0.05). Thus, larger pythons crawled more quickly, but because they had to crawl a longer distance to get off the road, total crossing time was similar across snake sizes0.053) live snakes per hour of survey.
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