Singing Behavior Leads to Detection Bias in a Territorial Songbird
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The development of models to account for variation in the probability of detection, such as N–mixture models, have advanced methods of estimating wildlife abundance and resource use. A core assumption of these models is that the detection of individuals is not influenced by conspecific density. A recent study of the Golden-cheeked Warbler, Setophaga chrysoparia, compared N–mixture model estimates of abundance to estimates of territory density based on spot mapping in each of six populations and demonstrated a negative density-dependent bias in N–mixture model estimates of abundance. Here we provide an indirect test of the assumption that detection of individuals is not influenced by conspecific density by investigating the singing behavior of male GCWA as a function of territory density within the same populations previously studied. Using automated recording units placed at randomly selected survey stations throughout the six study sites we found evidence of a significant positive effect of territory density on the average song rate per unit bird, measured as the number of songs recorded per 5 min, recorded per survey station. This pattern indicates that the number of opportunities to detect an individual (i.e. number of songs) within a survey interval is influenced by local territory density and documents a violation in this species of the implicit assumption of N–mixture models that the probability of detecting an individual is independent of the conspecific density. Failure to account for a density-detectability bias within the N–mixture model framework may result in biased estimates of occupancy or abundance.