Improving the precision of our ecosystem calipers: a modified morphometric technique for estimating marine mammal mass and body composition.

• Main Authors: Shero, Michelle R, Pearson, Linnea E, Costa, Daniel P, Burns, Jennifer M
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: eScholarship, University of California 2014
• Subjects: Animals; Mammals; Seals; Earless; Body Weight; Regression Analysis; Sample Size; Isotope Labeling; Ecosystem; Body Composition; Aquatic Organisms; General Science & Technology; Weddell; Weddell Seals
• Online Access: https://escholarship.org/uc/item/4b32z8t5

Mass and body composition are indices of overall animal health and energetic balance and are often used as indicators of resource availability in the environment. This study used morphometric models and isotopic dilution techniques, two commonly used methods in the marine mammal field, to assess body composition of Weddell seals (Leptonychotes weddellii, N = 111). Findings indicated that traditional morphometric models that use a series of circular, truncated cones to calculate marine mammal blubber volume and mass overestimated the animal's measured body mass by 26.9±1.5% SE. However, we developed a new morphometric model that uses elliptical truncated cones, and estimates mass with only -2.8±1.7% error (N = 10). Because this elliptical truncated cone model can estimate body mass without the need for additional correction factors, it has the potential to be a broadly applicable method in marine mammal species. While using elliptical truncated cones yielded significantly smaller blubber mass estimates than circular cones (10.2±0.8% difference; or 3.5±0.3% total body mass), both truncated cone models significantly underestimated total body lipid content as compared to isotopic dilution results, suggesting that animals have substantial internal lipid stores (N = 76). Multiple linear regressions were used to determine the minimum number of morphometric measurements needed to reliably estimate animal mass and body composition so that future animal handling times could be reduced. Reduced models estimated body mass and lipid mass with reasonable accuracy using fewer than five morphometric measurements (root-mean-square-error: 4.91% for body mass, 10.90% for lipid mass, and 10.43% for % lipid). This indicates that when test datasets are available to create calibration coefficients, regression models also offer a way to improve body mass and condition estimates in situations where animal handling times must be short and efficient.