Estimating repertoire size in a songbird: a comparison of three techniques. Issue 3 (1st September 2016)

• Record Type: Journal Article
• Authors: Harris, Alexander J.; Wilson, David R.; Graham, Brendan A.; Mennill, Daniel J.
• Is Part Of: Bioacoustics. Volume 25:Issue 3(2016:Sep.)
• Page Start: 211
• Page End: 224
• Publication Date: 2016-09-01
• Subjects: Capture–recapture -- coupon collector's problem -- curve fitting -- repertoire size -- simple enumeration -- vocal repertoire; Bioacoustics -- Periodicals; Sound production by animals -- Periodicals; Animal sounds -- Periodicals; Sound recordings -- Periodicals; 591.59405
• DOI: 10.1080/09524622.2016.1138416
• Languages: English
• ISSNs: 0952-4622

Abstract

Abstract: Many animals produce multiple types of breeding vocalizations that, together, constitute a vocal repertoire. In some species, the size of an individual's repertoire is important because it correlates with brain size, territory size or social behaviour. Quantifying repertoire size is challenging because the long recordings needed to sample a repertoire comprehensively are difficult to obtain and analyse. The most basic quantification technique is simple enumeration, where one counts unique vocalization types until no new types are detected. Alternative techniques estimate repertoire size from subsamples, but these techniques are useful only if they are accurate. Using 12 years of acoustic data from a population of rufous-and-white wrens in Costa Rica, we used simple enumeration to measure the repertoire size for 40 males. We then compared these to the estimates generated by three estimation techniques: curve fitting, capture–recapture and a new technique based on the coupon collector's problem. To understand how sampling effort affects the accuracy and precision of estimates, we applied each technique to six different-sized subsets of data per male. When averaged across subset sizes, the capture–recapture and coupon collector techniques showed the highest accuracy, whereas the curve fitting technique underestimated repertoire size. Precision (the average absolute difference between the estimated and true repertoire size) was significantly better for the capture–recapture technique than the coupon collector and curve fitting techniques. Both accuracy and precision improved as subset size increased. We conclude that capture–recapture is the best technique for estimating the sizes of small repertoires.