Faculty Research & Creative Activity

Document Type

Article

Publication Date

January 2012

Abstract

Although acoustic recordings have recently gained popularity as an alternative to point counts for surveying birds, little is known about the relative performance of the two methods for detecting tropical bird species across multiple vegetation types. During June and July 2008, we collected species detection/nondetection data to compare the performance of a quadraphonic acoustic recording system and point counts for estimating species richness and composition and detection probabilities of 15 rare, moderately common, and common tropical bird species across six structurally distinct vegetation types (coastal dune scrub, mangrove, low-stature deciduous thorn forest, early and late successional medium-stature semievergreen forest, and grazed pastures) in the northern Yucatan Peninsula.We selected five rare species endemic to the Yucatan Peninsula and 10 moderately common and common species that also occur in other tropical regions. Species richness and composition did not differ between survey methods in any of the vegetation types. At the population level, however, we found support for an effect of method on detection probability for most species. For 13 species, regardless of their abundance, acoustic recordings yielded detection probabilities as high as or higher than those for point counts across all vegetation types. The remaining two species were better detected by point counts in pastures and coastal scrub, where greater visibility likely improved sightings of these species. However, these species were detected as well as or better by acoustic recordings in forests and mangroves where detections were primarily auditory. In tropical regions where experienced field observersmay not be available and funding for field surveys may be limited, acoustic recordings offer a practical solution for determining species richness and composition and the occupancy patterns of most species. However, for some species, a combination of methods will provide the most reliable data. Regardless of the method selected, analyses that account for variation in detection probability among vegetation types will be necessary because most species in our study demonstrated vegetation-dependent detection probabilities.

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