Evaluation of distance estimation by observers with point counts and distance-sampling methodology: A field test

Abstract The distance-sampling methodology for estimating bird abundance assumes that distances between the observer and the birds are measured without error. Therefore, accurate distance estimates are crucial in bird surveys. Because most detections are based on auditory rather than visual observations (i.e., singing males, usually the easiest individuals to detect), estimating the distance to heard but unseen individuals is challenging and prone to error in dense, forest habitats. In this study, we evaluated the accuracy of distance estimation by observers under natural conditions in a temperate forest of the Białowieża National Park, Poland, by conducting qualitative “distance band tests” and quantitative “distance tests.” We found that probability of assigning an individual bird to the incorrect distance band (regardless of whether the distance was under- or overestimated) increased with distance. In quantitative tests, where we estimated the error in meters, both the frequency and magnitude of error also increased with distance. Underestimating distances (i.e., an individual was farther than the observer assumed) occurred more frequently than the opposite (i.e., an individual was closer than the observer’s assessment). While the magnitude and direction of errors varied between species, the consistent pattern for most species was that estimates were relatively accurate at closer distances but increasingly underestimated beyond ∼100 m. Seasonal changes in vegetation did not influence error probability or size. Distances to singing individuals were underestimated at significantly shorter distances for higher-frequency singers, while song amplitude showed an insignificant trend. Our findings underscore the need to account for distance estimation errors in avian population research, particularly when using distance sampling. The results also indicate that assigning an individual to a distance band instead of estimating exact distance may reduce errors. In temperate forests, making the most distant band sufficiently wide to reduce errors in assigning individuals to bands may also improve accuracy.