Distance sampling: comparing walked transects and road transects for rock ptarmigan densities and population trends
Matteo Ferrarini, Ólafur K. Nielsen
Abstract
Matteo Ferrarini, Ólafur K. Nielsen
Abstract
We compared population trends for rock ptarmigan Lagopus muta densities (2003‒2019) derived from walked transects and driven road transects in Mosfellsheiði and Slétta in southwest and northeast Iceland, respectively. The walked transects were laid out according to a random rule. Convenience‐based road transects could give biased population density estimates if roads affect the distribution of ptarmigan. We used distance sampling to compare density estimates provided by the two survey types. Our results showed that road transects were more than five times faster to conduct than walked transects. Estimated ptarmigan density changed in synchrony for the two survey methods in both study areas. Mean density estimates in Mosfellsheiði were similar for the two survey methods (walked transects 1.6 males × km −2 , 95% CI 1.4‒1.8; road transects 1.7 males × km −2 , 95% CI 1.4‒2.0), but not in Slétta, where density estimates for road transects were significantly lower (walked transects 5.2 males × km −2 , 95% CI 4.7‒5.7; road transects 3.2 males × km −2 , 95% CI 2.8‒3.7). Density estimates from the Slétta road transects were biased low because parts of the road intersected areas that ptarmigan did not occupy. This bias was remedied, at least partially, by considering the area of non‐habitats within the surveyed belt by applying multipliers in the distance analysis. Collectively, our results demonstrate that road‐based surveys and distance sampling can provide an economical means for estimating density and annual population trends for open country grouse (Tetraonini) like ptarmigan. Still, density estimates can be biased without proper consideration for survey design.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
We compared population trends for rock ptarmigan Lagopus muta densities (2003‒2019) derived from walked transects and driven road transects in Mosfellsheiði and Slétta in southwest and northeast Iceland, respectively. The walked transects were laid out according to a random rule. Convenience‐based road transects could give biased population density estimates if roads affect the distribution of ptarmigan. We used distance sampling to compare density estimates provided by the two survey types. Our results showed that road transects were more than five times faster to conduct than walked transects. Estimated ptarmigan density changed in synchrony for the two survey methods in both study areas. Mean density estimates in Mosfellsheiði were similar for the two survey methods (walked transects 1.6 males × km −2 , 95% CI 1.4‒1.8; road transects 1.7 males × km −2 , 95% CI 1.4‒2.0), but not in Slétta, where density estimates for road transects were significantly lower (walked transects 5.2 males × km −2 , 95% CI 4.7‒5.7; road transects 3.2 males × km −2 , 95% CI 2.8‒3.7). Density estimates from the Slétta road transects were biased low because parts of the road intersected areas that ptarmigan did not occupy. This bias was remedied, at least partially, by considering the area of non‐habitats within the surveyed belt by applying multipliers in the distance analysis. Collectively, our results demonstrate that road‐based surveys and distance sampling can provide an economical means for estimating density and annual population trends for open country grouse (Tetraonini) like ptarmigan. Still, density estimates can be biased without proper consideration for survey design.
Key concepts: Transect, Distance sampling, Belt transect, Sampling (signal processing), Geography, Population density, Population, Physical geography