Using Binomial Distance-Sampling Models to Estimate the Effective Detection Radius of Point-Count Surveys Across Boreal Canada

ABSTRACT. We used binomial distance-sampling models to estimate the effective detection radius (EDR) of point-count surveys across boreal Canada. We evaluated binomial models based on 0–50 m and >50 m distance categories for goodness-of-fit and sensitivities to variation in survey effort and habitats sampled. We also compared binomial EDRs to Partners in Flight's maximum detection distances (MDD) to determine differences in landbird population sizes derived from each. Binomial EDRs had a small positive bias (4%) averaged across 86 species and a large positive bias (30–82%) for two species when compared with EDRs estimated using multinomial distance sampling. Patterns in binomial EDRs were consistent with how bird songs attenuate in relation to their frequencies and transmission through different habitats. EDR varied 12% among habitats and increased 17% when birds were counted to an unlimited distance, compared with a limited distance of 100 m. The EDR did not vary with the duration of surveys, and densities did not differ when using unlimited-distance versus truncated data. Estimated densities, however, increased 19% from 3- to 5-min counts and 25% from 5- to 10-min counts, possibly from increases in the availability, movement, or double counting of birds with longer counts. Thus, investigators should be cautious when comparing distance-sampling results among studies if methods vary. Population sizes estimated using EDR averaged 5 times (0.8–15 times) those estimated with MDD. Survey data from which to estimate binomial EDRs are widely available across North America and could be used as an alternative to MDD when estimating landbird population sizes.