Comparing Uncertainty Associated With 1-, 2-, and 3D Aerial Photogrammetry-Based Body Condition Measurements of Baleen Whales

K C Bierlich,Andrew J Read,Joshua Hewitt,Robert S Schick,Ari Friedlaender,Leigh G Torres,David W Johnston,Clara N Bird,John Calambokidis,Julian Dale,Jeremy Goldbogen

doi:10.3389/fmars.2021.749943

Abstract

Body condition is a crucial and indicative measure of an animal’s fitness, reflecting overall foraging success, habitat quality, and balance between energy intake and energetic investment toward growth, maintenance, and reproduction. Recently, drone-based photogrammetry has provided new opportunities to obtain body condition estimates of baleen whales in one, two or three dimensions (1D, 2D, and 3D, respectively) – a single width, a projected dorsal surface area, or a body volume measure, respectively. However, no study to date has yet compared variation among these methods and described how measurement uncertainty scales across these dimensions. This associated uncertainty may affect inference derived from these measurements, which can lead to misinterpretation of data, and lack of comparison across body condition measurements restricts comparison of results between studies. Here we develop a Bayesian statistical model using known-sized calibration objects to predict the length and width measurements of unknown-sized objects (e.g., a whale). We use the fitted model to predict and compare uncertainty associated with 1D, 2D, and 3D photogrammetry-based body condition measurements of blue, humpback, and Antarctic minke whales – three species of baleen whales with a range of body sizes. The model outputs a posterior predictive distribution of body condition measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty. We find that uncertainty does not scale linearly across multi-dimensional measurements, with 2D and 3D uncertainty increasing by a factor of 1.45 and 1.76 compared to 1D, respectively. Each standardized body condition measurement is highly correlated with one another, yet 2D body area index (BAI) accounts for potential variation along the body for each species and was the most precise body condition metric. We hope this study will serve as a guide to help researchers select the most appropriate body condition measurement for their purposes and allow them to incorporate photogrammetric uncertainty associated with these measurements which, in turn, will facilitate comparison of results across studies.

Highlights

An animal’s body condition is a crucial and indicative measure of its fitness, as it reflects the balance between energy intake and energetic investment in growth, maintenance, and reproduction (Jakob et al, 1996; Schulte-Hostedde et al, 2001)
The four objectives of the present study are to: (1) apply methods described in Bierlich et al (2021) to incorporate uncertainty associated with multiple measurements of the same individual from image(s) to estimate the body condition of blue, humpback and minke whales; (2) compare how uncertainty scales across 1D, 2D, and 3D body condition measurements of these estimates; (3) compare precision in the posterior predictive distributions for each body condition estimate; and (4) compare how body condition indices are correlated for these species
single width (SW), surface area (SA), and body volume (BV) increased as the total length (TL) increased for each species, while SWstd and Body area index (BAI) did not because they are standardized by TL (Figure 4)

Summary

Introduction

An animal’s body condition is a crucial and indicative measure of its fitness, as it reflects the balance between energy intake and energetic investment in growth, maintenance, and reproduction (Jakob et al, 1996; Schulte-Hostedde et al, 2001). Unoccupied aircraft systems (UAS or drones) have greatly increased the capacity to obtain body condition measurements from aerial imagery to monitor baleen whale populations, especially in their role as ecosystem sentinels (Johnston, 2019; Castrillon and Bengtson Nash, 2020). These platforms are safer, yield higher resolution data, and are more accurate, immediate, and affordable compared to using traditional camera systems mounted on airplanes. Several different photogrammetry-based methods for measuring body condition have emerged from these studies and, as Castrillon and Bengtson Nash (2020) argue, a standardization of measurements across studies is needed and uncertainty should be both quantified and minimized, as a measurement result is complete only when accompanied by a quantitative statement of its uncertainty (Taylor and Kuyatt, 1994)

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