DOI: 10.5061/dryad.d51c5b07p
title: Quantifying the age-structure of free-ranging delphinid populations: testing the accuracy of Unoccupied Aerial System-photogrammetry

description: Understanding the population health status of long-lived and
 slow-reproducing species is critical for their management. However, it can
 take decades with traditional monitoring techniques to detect
 population-level changes in demographic parameters. Early detection of the
 effects of environmental and anthropogenic stressors on vital rates would
 aid in forecasting changes in population dynamics and therefore inform
 management efforts. Changes in vital rates strongly correlate with
 deviations in population growth, highlighting the need for novel
 approaches that can provide early warning signs of population decline
 (e.g., changes in age-structure). We tested a novel and frequentist
 approach, using Unoccupied Aerial System- (UAS) photogrammetry, to assess
 the population age-structure of small delphinids. First, we measured the
 precision and accuracy of UAS-photogrammetry in estimating total body
 length (TL) of trained bottlenose dolphins (Tursiops truncatus). Using a
 log-transformed linear model, we estimated TL using the
 blowhole-to-dorsal-fin-distance (BHDF) for surfacing animals. To test the
 performance of UAS-photogrammetry to age-classify individuals, we then
 used length measurements from a 35-year dataset from a free-ranging
 bottlenose dolphin community to simulate UAS-estimates of BHDF and TL. We
 tested five age-classifiers and determined where young individuals
 (&lt;10 years) were assigned when misclassified. Finally, we tested
 whether UAS-simulated BHDF only or the associated TL estimates provided
 better classifications. TL of surfacing dolphins was overestimated by 3.3%
 ±3.1% based on UAS-estimated BHDF. Our age-classifiers performed best in
 predicting age-class when using broader and fewer (two and three)
 age-class bins with ~80% and ~72% assignment performance, respectively.
 Overall, 72.5-93% of the individuals were correctly classified within two
 years of their actual age-class bin. Similar classification performances
 were obtained using both proxies. UAS-photogrammetry is a non-invasive,
 inexpensive, and effective method to estimate TL and age-class of
 free-swimming dolphins. UAS-photogrammetry can facilitate the detection of
 early signs of population changes, which can provide important insights
 for timely management decisions.
description: We physically measured TL
 (i.e., the tip of the rostrum to the tip of the natural notch created by
 the overlapping fluke lobes, hereafter referred to as the notch) and BHDF
 for 18 bottlenose dolphins under human care at two facilities in Hawaiʻi,
 USA. The distance from the center of the blowhole to the anterior
 insertion of the dorsal fin (BHDF) is an established proxy for TL in
 bottlenose dolphins (Cheney et al., 2018; van Aswegen et al.,
 2019). Six adult males
 ranging from 11.5 to 34.5
 years of age (mean = 23.6 ±7.9 years) at Dolphin Quest Oʻahu (DQO); HI,
 USA, were measured in June 2019. Six females and six males ranging from
 4.0 to 49.0 years of age (mean = 17.4 ± 14.8 years) at Dolphin Quest
 Hawaiʻi (DQH); HI, USA, were measured in August–October 2019. The date of
 birth (DOB) of the 14 individuals born in facilities is known. The other
 four individuals (two males and two females) were born in the Gulf of
 Mexico. The age of these animals was based on the size that they were when
 collected. Dolphins were measured in a stationary and straight position
 for all measurements. TL was collected on the ventral side of the dolphin
 in an inverted position using a tape measure attached to a rigid PVC pipe.
 The base of the measuring pipe was placed onto a rigid plate aligned with
 the tip of the rostrum to allow for straight-line measurements. BHDF
 measurements were made from the center of the blowhole to the insertion of
 the dorsal fin using a soft measuring tape. One measurement set
 (consisting of 2–3 replicates per measurement) was collected on the day or
 within a week of the UAS sampling. To increase sample size, 4–6 additional
 replicates were collected within the next seven months (total of 7–10 TL
 and BHDF measurements per animal). DQH measurements per animal were
 collected on the same day. A DJI Inspire-2 quadcopter was used to collect
 aerial imagery. The Inspire-2 was equipped with a DJI Zenmuse X5s digital
 camera (20.8-megapixel, Micro Four Thirds format; calibrated following
 Dawson et al.
 (2017)) with an Olympus
 M.Zuiko 25 mm f/1.8 lens. A LightWare SF11/C laser altimeter
 (Dawson et al.,
 2017) was attached,
 providing an accuracy of 0.1 m and resolution of 1 cm. Despite the
 precision, some inaccurate altitude readings were recorded. To correct
 these errors, a custom-made smoother was applied to the original data. The
 Inspire-2 recorded videos in 4k resolution (3840x2150 pixels). Consecutive
 flights using both platforms (n=24 flights in total) were conducted at five
 altitudes (16m, 20m, 30m, 40m and 50m). 
 Dolphins were sampled under
 two scenarios: stationary and positioned flat and straight in the water
 and with the slight arching that occurs when surfacing naturally while
 swimming. Stationary animals were supported by husbandry staff under the
 caudal region to maintain the body straight and the fluke flat.
 Photogrammetry of stationary behaviors was collected to compare UAS
 measurements of TL and BHDF (Fig. 2) with the respective physical
 measurements. A target of three images was selected per
 individual, altitude, and behavior (i.e., stationary and surfacing)
 combination. Images were extracted using VLC Media Player Software
 (VideoLAN). For surfacing dolphins, video stills and photographs were
 selected when both the blowhole and dorsal fin insertion were visible and
 when the individual’s body was as straight and horizontal as possible
 (i.e., minimal body arch). Available images of sufficient quality varied
 by platform. In total, 144 video stills (75 stationary and 69 surfacing)
 of sufficient quality were used. Due to weather or the lack of images of
 sufficient quality,  individual F was removed from the
 analyses.
description: Any image viewer software Microsoft Excel