Downsized: gray whales using an alternative foraging ground have smaller morphology

Abstract

Describing individual morphology and growth is key for identifying ecological niches and monitoring the health and fitness of populations. Eastern North Pacific ((ENP), approximately 16 650 individuals) gray whales primarily feed in the Arctic/sub-Arctic regions, while a small subgroup called the Pacific Coast Feeding Group (PCFG, approximately 212 individuals) instead feeds between northern California, USA and British Columbia, Canada. Evidence suggests PCFG whales have lower body condition than ENP whales. Here we investigate morphological differences (length, skull, and fluke span) and compare length-at-age growth curves between ENP and PCFG whales. We use ENP gray whale length-at-age data comprised of strandings, whaling, and aerial photogrammetry (1926–1997) for comparison to data from PCFG whales collected through non-invasive techniques (2016–2022) to estimate age (photo identification) and length (drone-based photogrammetry). We use Bayesian methods to incorporate uncertainty associated with morphological measurements (manual and photogrammetric) and age estimates. We find that while PCFG and ENP whales have similar growth rates, PCFG whales reach smaller asymptotic lengths. Additionally, PCFG whales have relatively smaller skulls and flukes than ENP whales. These findings represent a striking example of morphological adaptation that may facilitate PCFG whales accessing a foraging niche distinct from the Arctic foraging grounds of the broader ENP population.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 01, 2023
Source ID
10.1098/rsbl.2023.0043

Entities

People

  • Alejandro Fernández Ajó
  • Alexander A. Kane
  • Clara N. Bird
  • I. Hildebrand
  • James L. Sumich
  • Joshua D. Stewart
  • Joshua Hewitt
  • K C Bierlich
  • Leigh G Torres
  • Lisa Hildebrand

Organizations

  • Duke University
  • Office of Naval Research
  • Oregon Sea Grant
  • Oregon State University

Tags

Fields of Study

  • Environmental science

Readers

  • Economics
  • Marine Mammal Biology
  • Materials Science.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy