Spy in the sky: a method to identify pregnant small cetaceans

Data on sex ratios, age classes, reproductive success and health status are key metrics to manage populations yet can be difficult to collect in wild cetacean populations. Long-term individual-based studies provide a unique opportunity to apply unoccupied aerial system (UAS) photogrammetry to non-invasively measure body morphometrics of individuals with known life history information. The aims of this study were 1) to compare length measurements from UAS photogrammetry with laser photogrammetry and 2) to explore whether UAS measurements of body width could be used to remotely determine pregnancy status, sex or age class in a well-studied bottlenose dolphin population in Scotland. We carried out five boat-based surveys in July and August 2017, with concurrent photo-identification, UAS, and laser photogrammetry. Photographs were measured using bespoke programmes, MorphMetriX for UAS photos and a Zooniverse project for laser photos. In total 64 dolphins were identified using photo-ID, 54 of which had concurrent UAS body length and 47 with laser body length measurements. We also measured body widths at 10% increments from 10-90% of body length for 48 individuals of known sex, age class and/or pregnancy status. There was no significant difference in the length of individuals measured with UAS and laser photogrammetry. Discriminant analyses of the body width-length ratios expected to change during pregnancy, correctly assigned pregnancy status for 14 of the 15 females of known pregnancy status. Only one pregnant female was incorrectly assigned as not pregnant. However, our results showed that length and body width cannot accurately allocate these bottlenose dolphins to sex or age class using photogrammetry techniques alone. The present study illustrates that UAS and laser photogrammetry measurements are comparable for small cetaceans and demonstrates that UAS measurements of body width-length ratio can accurately assign pregnancy status in bottlenose dolphins.Data consist of 4 files and include the datasets and R code required to repeat all the analyses. 1. UAV Analyses in R.txt: R code to summarise the data and carry out all the analyses in the manuscript. 2. UAV_Measured_Images.csv : Total length and width measurements of the bottlenose dolphins photographed and identified in UAS photogrammetry surveys. 3. UAV_Laser_Zooniverse_Measurements.csv: Laser photogrammetry measurements of the bottlenose dolphins measured using Zooniverse. 4. ID.csv: Known life history information of each bottlenose dolphin. 5. README.txt: Details of the data in the csv files