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Robust age estimation of southern sea otters from multiple morphometrics

Authors :
Teri E. Nicholson
Karl A. Mayer
Michelle M. Staedler
Tyler O. Gagné
Michael J. Murray
Marissa A. Young
Joseph A. Tomoleoni
Martin Tim Tinker
Kyle S. Van Houtan
Source :
Ecology and Evolution, Vol 10, Iss 16, Pp 8592-8609 (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Abstract Reliable age estimation is an essential tool to assess the status of wildlife populations and inform successful management. Aging methods, however, are often limited by too few data, skewed demographic representation, and by single or uncertain morphometric relationships. In this study, we synthesize age estimates in southern sea otters Enhydra lutris nereis from 761 individuals across 34 years of study, using multiple noninvasive techniques and capturing all life stages from 0 to 17 years of age. From wild, stranded, and captive individuals, we describe tooth eruptions, tooth wear, body length, nose scarring, and pelage coloration across ontogeny and fit sex‐based growth functions to the data. Dental eruption schedules provided reliable and identifiable metrics spanning 0.3–9 months. Tooth wear was the most reliable predictor of age of individuals aged 1–15 years, which when combined with total length, explained >93% of observed age. Beyond age estimation, dental attrition also indicated the maximum lifespan of adult teeth is 13‒17 years, corresponding with previous estimates of life expectancy. Von Bertalanffy growth function model simulations of length at age gave consistent estimates of asymptotic lengths (male Loo = 126.0‒126.8 cm, female Loo = 115.3‒115.7 cm), biologically realistic gestation periods (t0 = 115 days, SD = 10.2), and somatic growth (male k = 1.8, SD = 0.1; female k = 2.1, SD = 0.1). Though exploratory, we describe how field radiographic imaging of epiphyseal plate development or fusions may improve aging of immature sea otters. Together, our results highlight the value of integrating information from multiple and diverse datasets to help resolve conservation problems.

Details

Language :
English
ISSN :
20457758
Volume :
10
Issue :
16
Database :
Directory of Open Access Journals
Journal :
Ecology and Evolution
Publication Type :
Academic Journal
Accession number :
edsdoj.7e6e0b28d81b4aa1bf21c0385a184461
Document Type :
article
Full Text :
https://doi.org/10.1002/ece3.6493