Noninvasive unmanned aerial vehicle provides estimates of the energetic cost of reproduction in humpback whales

Abstract An animal's body condition will affect its survival and reproductive success, which influences population dynamics. Despite its importance, relatively little is known about the body condition of large whales and its relationship to reproduction. We assessed the body condition of humpback whales ( Megaptera novaeangliae ) at a breeding/resting ground from aerial photographs recorded using an unmanned aerial vehicle ( UAV ). Photogrammetry methods were used to measure the surface area of individual whales, which was used as an index for body condition. Repeated measurements of the same individuals were not possible; hence, this study represents a cross‐sectional sample of the population. Intraseasonal changes in the body condition of four reproductive classes (calves, immature, mature, and lactating) were investigated to infer the relative energetic cost that each class faces during the breeding season. To better understand the costs of reproduction, we investigated the relationship between female body condition ( FBC ) and the linear growth and body condition of their dependent calves ( CBC ). We documented a linear decline in the body condition of mature whales (0.027 m 2 /d; n = 20) and lactating females (0.032 m 2 /d; n = 31) throughout the breeding season, while there was no change in body condition of immature whales ( n = 51) and calves ( n = 32). The significant decline in mature and lactating female's body condition implies substantial energetic costs for these reproductive classes. In support of this, we found a positive linear relationship between FBC and CBC . This suggests that females in poorer body condition may not have sufficient energy stores to invest as much energy into their offspring as better conditioned females without jeopardizing their own body condition and survival probability. Measurement precision was investigated from repeated measurements of the same animals both from the same and different photographs, and by looking at residual errors in relation to the positioning of the whales in the photographs. The resulting errors were included in a sensitivity analysis to demonstrate that model parameters were robust to measurement errors. Our findings provide strong support for the use of UAV s as a noninvasive tool to measure the body condition of whales and other mammals.