Estimation of avian species richness: biases in morning surveys and efficient sampling from acoustic recordings

Species richness estimation is an important component of ecological studies and conservation planning. Limited resources necessitate that sampling protocols be as efficient and accurate as possible. For birds, automated acoustic sampling offers potential advantages of abundant data at reduced cost for field observers, and enhanced diel coverage, but neither of which may accrue if surveys are biased and/or too costly to analyze in the lab. Here, we assessed bias in estimates of species and higher order taxonomic richness obtained from standard morning point counts, and from morning-only acoustic recordings, relative to estimates from 72, 10-min acoustic recordings conducted hourly over 3 d. Furthermore, we compared 10-min subsamples of 24-h recordings across five statistical estimators to establish which combination of number of samples, from which times of day, and with which statistical estimator, best approximated total observed species richness. Total observed species richness was the total number of species detected per site over 720 min of 10-min recordings. Standard morning point counts and morning-only acoustic recordings consistently underestimated both total species and higher order taxonomic richness. Species not detected were those that irregularly or nocturnally vocalize. Without statistical estimators, the greatest number of species per unit sample effort was detected from 10-min, on-the-hour samples between 07:00 and 12:00, and at 21:00, over 3 d. With the jackknife estimator, three 10-min samples (one at each of 08:00, 09:00, and 12:00, over 3 d) most efficiently estimated within 5% of total observed species richness. Researchers can subsample in combination with statistical estimators to increase analytical efficiency for species richness using acoustic recordings.