Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping

Abstract

Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping. Nature Conservation 7: 1-13. doi: 10.3897/natureconservation.7.6890 Abstract Population size assessments for nocturnal burrow-nesting seabirds are logistically challenging because these species are active in colonies only during darkness and often nest on remote islands where manual inspections of breeding burrows are not feasible. Many seabird species are highly vocal, and recent technological innovations now make it possible to record and quantify vocal activity in seabird colonies. Here we test the hypothesis that remotely recorded vocal activity in Cory's shearwater (Calonectris borealis) breeding colonies in the North Atlantic increases with nest density, and combined this relationship with cliff habitat mapping to estimate the population size of Cory's shearwaters on the island of Corvo (Azores). We deployed acoustic recording devices in 9 Cory's shearwater colonies of known size to establish a relationship between vocal activity and local nest density (slope = 1.07, R 2 = 0.86, p < 0.001). We used this relationship to predict the nest density in various cliff habitat types and produced a habitat map of breeding cliffs to extrapolate nest density around the island of Corvo. The mean predicted nest density on Corvo ranged from 6.6 (2.1-16.2) to 27.8 (19.5-36.4) nests/ha. Extrapolation of habitat-specific nest densities across the cliff area of Corvo resulted in an estimate of 6326 Cory's shearwater nests (95% confidence interval: 524). This population size estimate is similar to previous assessments, but is too imprecise to detect moderate changes in population size over time. While estimating absolute population size from acoustic recordings may not be sufficiently precise, the strong positive relationship that we found between local nest density and recorded calling rate indicates that passive acoustic monitoring may be useful to document relative changes in seabird populations over time. RESEARCH ARTICLE Launched to accelerate biodiversity conservation A peer-reviewed open-access journalSteffen Oppel et al. / Nature Conservation 7: 1-13 (2014) 2

Acoustic activity across a seabird colony reflects patterns of within‐colony flight rather than nest density

“…Several previous studies in closely related procellariforms, with similar call amplitudes and breeding habitats, found that Wildlife Acoustic's Song Meter units can record vocalizations up to 50 m away (Buxton & Jones , Oppel et al . , Dufour et al . ).…”

“…The importance of controlling for these factors that affect the soundscape, and the detectability of a species’ vocalizations, has been discussed in detail in the literature (Buxton & Jones , Oppel et al . ) and should be considered when studying biophony within a soundscape.…”

Efficient sampling of avian acoustic recordings: intermittent subsamples improve estimates of single species prevalence and total species richness

“…This translates to a 19% reduction in standard errors around the mean and an increase in statistical power equivalent to increasing a survey's sample size (n) by a factor of 1.52, i.e., (1-0.19) -2 , assuming samples are truly independent of one another. Given call rates (and other similar measures of vocal activity) are often used as indices of abundance (Sepúlveda et al 2006, Borker et al 2014, Oppel et al 2014 greater statistical power will translate into an enhanced ability to detect differences in abundance between two different places or across different years. This is of particular importance for scientists attempting to understand ecological processes and conservation practitioners whose management Fig.…”

Comparison of autonomous and manual recording methods for discrimination of individually distinctive Ovenbird songs

“…This study adds to the growing utility of off-the shelf automated recording systems such as Wildlife Acoustics SM2 recorders which include long-term monitoring of vocal behaviour (Bruni and Foote 2014), estimating population size (Oppel et al 2014), calculations of species richness (Haselmayer and Quinn 2000), species at risk monitoring (Holmes et al 2014) and the ability to localize sounds (Mennill et al 2012). Information about individuals obtained from automated recordings will provide important insights in the study of behaviour and conservation of species, particularly those more sensitive to human disturbance.…”