Auk’s Top Cited, #5: Estimating Detection Probability During Point Counts

Fig3 new

Modeled relationships between covariates and predicted abundance per point for Willow Ptarmigan (WIPT) and Rock Ptarmigan (ROPT) observed during point-transect surveys in southwest Alaska.

This week we highlight a paper from the October 2014 issue of The AukA hierarchical model combining distance sampling and time removal to estimate detection probability during avian point counts by C.L. Amundson, J.A. Royle, and C.M. Handel.

Imperfect detection during surveys such as point counts biases estimates of abundance. To address this, models have been developed to account for availability (the probability that an animal is available for detection; e.g., that a bird sings) and perceptibility (the probability that an observer detects an animal). Amundson, Royle, and Handel took this a step further, developing a hierarchical extension of the combined model that provides a framework for a collection of survey points at which both distance from the observer and time of initial detection are recorded.

They first tested their proposed model using simulated data, and then took it into the field with surveys of Golden-crowned Sparrows and ptarmigans. Their results suggest that this model can provide insight into the detection process during avian surveys and reduce bias in estimates of relative abundance, but is best applied to surveys of species with greater availability—precision was reduced with ptarmigans, which give only intermittent, primarily visual cues to their presence.

Read the full study at

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