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.
Keywords
binomial distance-sampling models, boreal forest birds, density estimation, detection probabilities, effective detection radius, point-count surveys, population size estimation
Nincsenek megjegyzések:
Megjegyzés küldése