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Data from: Estimating bird detection distances in sound recordings for standardising detection ranges and distance sampling

Cite this dataset

Darras, Kevin et al. (2018). Data from: Estimating bird detection distances in sound recordings for standardising detection ranges and distance sampling [Dataset]. Dryad. https://doi.org/10.5061/dryad.h0qg353

Abstract

1) Autonomous sound recorders are increasingly used to survey birds, and other wildlife taxa. Species richness estimates from sound recordings are usually compared with estimates obtained from established methods like point counts, but so far the comparisons were biased: Detection ranges usually differ between the survey methods, and bird detection distance data are needed for standardizing data from sound recordings. 2) We devised and tested a method for estimating bird detection distances from sound recordings, using a reference recording of test sounds at different frequencies, emitted from known distances. We used our method to estimate bird detection distances in sound recordings from tropical forest sites where point counts were also used. We derived bird abundance and richness measures and compared them between point counts and sound recordings using unlimited radius and fixed radius counts, as well as distance sampling modelling. 3) First we show that it is possible to accurately estimate bird detection distances in sound recordings. We then demonstrate that these data can be used to standardize the detection ranges between point counts and sound recordings with a fixed-radius approach, leading to higher abundance and richness estimates for sound recordings. Our distance-sampling approach also revealed that sound recorders sampled significantly higher bird densities than human point counts. 4) We show for the first time that it is possible to standardize detection ranges in sound recordings and that distance sampling can successfully be used too. We revealed that birds were flushed by human observers and that this possibly leads to lower density estimates in point counts, although sound recorders could also have sampled more birds because of their earlier deployment times. Sound recordings are more amenable to distance-sampling modelling than point counts as they do not exhibit an observer-induced avoidance effect, and they can easily collect more replicates for obtaining more accurate bird density estimates. Quantifying bird detection distances was so far one important shortcoming that hindered the adoption of modern autonomous sound recording methods for ecological surveys.

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