Monitoring pregnancy rates can provide vital information regarding a population’s viability and trajectory. This study combined drone-based photogrammetry with biopsy darting to determine if the Scaled Mass Index (SMI) estimated from aerial images can be used to identify pregnant, free-ranging St. Lawrence Estuary belugas (Delphinapterus leucas). To identify reproductive status while minimizing tissue usage, liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was first compared to a previously validated ELISA method, before being used to measure progesterone in outer blubber layer of free-ranging females (n = 37) biopsied 4–5 months post-mating. Progesterone levels from these animals were then merged with those obtained from 65 previously sampled females (progesterone quantified via ELISA) to develop a two-cluster mixture model predicting individual reproductive status. This study demonstrated the suitability of progesterone levels determined using UPLC-MS/MS at detecting pregnancy in free-ranging cetaceans, and provided a statistical framework for merging hormone datasets generated using different analytical methods. No correlation was found between the SMI and pregnancy probability, suggesting that body shape changes indicative of pregnancy may not be detectable in the early stages of gestation. However, these results provide a basis for the development of a non-invasive photogrammetry-based method for detecting pregnancies during later stages of gestation. 

Please do not hesitate to contact me at sherrill.meredith@courrier.uqam.ca for a copy of the paper.