Published April 4, 2018 | Version 1.0

Acoustic Spatial Capture-Recapture (aSCR) and the Cryptic Cape Peninsula Moss Frog Arthroleptella lightfooti Metadata

Authors/Creators

  • 1. Stellenbosch University

Contributors

Supervisor:

  • 1. C·I·B, Department of Botany & Zoology, Stellenbosch University

Description

All the raw data and some of the processed data (up until the completion of the MSc) for the aSCR MSc by Marike Louw is in this repository. The raw data includes the raw recordings, datasheets from the field and the "estlocs" files from distances and array configurations from the field. There are fewer estimated density results of Arthroleptella lightfooti than there are raw recordings as all the analyses through aSCR could not be completed within the time of a MSc degree. ABSTRACT: Qualitative measurements of wildlife populations, such as population density, are quintessential for management and conservation. Acoustic Spatial Capture-recapture (aSCR) is a technique that is used to estimate the densities of acoustically active animals. It is advantageous to use when animals defy the use of traditional methods of population estimation by being very visually cryptic, but remaining acoustically active. Arthroleptella lightfooti is a visually cryptic moss frog with an average snout to vent length of 14.5 mm. The males call during the austral winter from seepages within a restricted range across the Cape Peninsula. The species has an IUCN status of Near Threatened. Here, the population densities of the endemic A. lightfooti are estimated across their range on the Cape Peninsula for the first time using aSCR. Multiple microphones, termed "acoustic arrays", are deployed in the field to record the calls of the frogs. I assess the use of aSCR in terms of reliability of the density estimates by examining the standard errors as coefficients of variation (CVs) of the density estimates. A density estimate with a CV above 30% was considered unreliable. Recording calls for the aSCR analyses involved visiting more than 200 sites during 2016 and 2017, and deploying acoustic arrays at a total of 149 sites, of which a subset of 85 sampling sites was used. I examined the influence of different variables on the size of the CV, namely: the average number of calls received by the acoustic array per minute, the array formation, and the detector frequencies (the combination of different numbers of microphones across which calls were heard). In addition, I made use of an output from aSCR that is an aerial view of the estimated calling locations of frogs relative to the acoustic arrays. I overlaid this output with aerial images taken at three different sites using a drone, and I examined the microhabitat features that relate most significantly to the presence of calling A. lightfooti. When there were less than 111call.min-1 received by the array, density estimates had CVs that exceeded 30% and were therefore considered unreliable. Above this threshold, 91% of density estimates were acceptable. When calls were heard on mostly one microphone, and decreasingly heard across two, three, four, five and six microphones, the density estimates were more reliable. However, when calls were mostly picked up across a combination of one and six microphones, density estimates became less reliable. This suggests that array formations should have the microphones spaced in such a way that not all calls are detected across all the microphones or only one microphone. The presence of calling frogs was significantly related to the presence of wet, seepy patches in the microhabitat and to the absence of standing water. This is consistent with observations in the field and reflects the biological needs of the species: it has no life stages in water but needs moist areas for eggs and tadpoles to develop. The successful application of aSCR to A. lightfooti is promising in the field of population studies on cryptic species, as it can be used to evaluate the populations of other calling taxa, which holds important implications for conservation and management.

Notes

The raw recordings can be rerun if improved sound extraction processes are found. The processed recordings can then be rerun through the latest aSCR models. The files in this repository can be used to rerun aSCR models if wanted.

Files

CDC_part_1.zip

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