Open AccessPhoto-identification of individual Southern Hemisphere humpback whales (Megaptera novaeangliae) using all available natural marks:
Author(s) -
Trish Franklin,
Wally Franklin,
Lyndon O Brooks,
Peter Lynton Harrison,
Dan Burns,
Jason Holmberg,
John Calambokidis
Publication year - 2020
Publication title -
the journal of cetacean research and management
Language(s) - English
Resource type - Journals
eISSN - 2312-2692
pISSN - 1561-0713
DOI - 10.47536/jcrm.v21i1.186
Subject(s) - humpback whale , dorsal fin , dorsum , population , southern hemisphere , biology , fishery , geography , whale , ecology , anatomy , demography , sociology
Misidentification errors in capture-mark recapture studies of humpback whales (Megaptera novaeangliae) related to poor quality of photographs as well as changes in natural marks can seriously affect population dynamics parameter estimates and derived estimates of population size when using sophisticated modelling techniques. In this study we used an innovative photo-identification matching system to investigate and examine the long-term stability and/or changes in natural marks on ventral-tail flukes, dorsal fin shapes and lateral body marks from a sample of 79 individual humpback whales, resighted in 2 to 11 years over timespans ranging from 2 to 21 years. A binary logistic mixed effects model, on a pair-matched sample of the 79 individual whales, found no significant differences in the proportions of ventral-tail fluke marks, dorsal fin shapes and lateral body marks, that displayed changes in primary and/or secondary characteristics over years (F=0.939, df=1/156, p =0.334). The results of this study substantiate the value and reliability of using primary and secondary natural marks on the ventral-tail flukes, in conjunction with dorsal fin shapes and secondary lateral body marks as double-tags. This provides a means of maximising observations of individual humpback whales over years, while minimising and managing misidentification errors in the photo-identification matching process, thus significantly improving modelling outcomes.