Understanding detection distances of avian vocalizations using automated recording units.
Supervised by Dr. Erin Bayne
Standardized count methods have been utilized since the late 70s – early 80s to census avian populations. However, count data provides estimates of relative abundance and species richness, and can be easily misinterpreted when using them as a population index from which to draw inferences. Raw count data is often closely associated with true abundance and density although it does not account for variation in the probability of detection. For acoustic counts, this variation comes from factors affecting sound transmission properties of animal vocalizations. Therefore, my research goals are to 1) investigate variation in transmission of animal vocalizations due to species- and habitat-specific characteristics, and 2) use this variation by species and habitat to estimate population densities of target species using established density modelling methods. This research will aid in efficient acoustic monitoring and assessment of avian populations by increasing spatial and temporal census coverage in under sampled regions, increasing accuracy of population estimates, and increasing our knowledge of rare and poorly assessed species.