[MARMAM] New publication: Comparing Uncertainty Associated With 1-, 2-, and 3D Aerial Photogrammetry-Based Body Condition Measurements of Baleen Whales

Bierlich, Kevin C kevin.bierlich at oregonstate.edu
Mon Nov 29 08:24:39 PST 2021


Hi there MARMAM Community,

On behalf of my colleagues, I am pleased to share our recent publication in Frontiers in Marine Science:

Bierlich KC, Hewitt J, Bird CN, Schick RS, Friedlaender A, Torres LG, Dale J, Goldbogen J, Read AJ, Calambokidis J and Johnston DW (2021) Comparing Uncertainty Associated With 1-, 2-, and 3D Aerial Photogrammetry-Based Body Condition Measurements of Baleen Whales. Front. Mar. Sci. 8:749943. 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.

This article is open-access and available at:
https://www.frontiersin.org/articles/10.3389/fmars.2021.749943/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Marine_Science&id=749943


Cheers,
KC

KC (Kevin) Bierlich, PhD, MEM
Postdoctoral Scholar
Geospatial Ecology of Marine Megafauna (GEMM<https://mmi.oregonstate.edu/gemm-lab>) Lab
Marine Mammal Institute | Dept. of Fisheries, Wildlife, & Conservation Sciences
Oregon State University
Pronouns: he, him, his
kcbierlich.com<https://www.kcbierlich.com>
kevin.bierlich at oregonstate.edu<mailto:kevin.bierlich at oregonstate.edu>













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