Document
Molecular ecology meets remote sensing : environmental drivers to population structure of humpback dolphins in the Western Indian Ocean.
Identifier
DOI: 10.1038/hdy.2011.21
Contributors
Subramaniam, A., Author
Collins, T., Author
Minton, G., Author
Baldwin, R., Author
Berggren, P., Author
Sarnblad, A., Author
Amir, O. A., Author
Peddemors, V. M., Author
Karczmarski, L., Author
Guissamulo, A., Author
Rosenbaum, H. C., Author
Publisher
Macmillan Publishers.
Gregorian
2011-10
Language
English
Subject
English abstract
Genetic analyses of population structure can be placed in explicit environmental contexts if appropriate environmental data are available. Here, we use high-coverage and high-resolution oceanographic and genetic sequence data to assess population structure patterns and their potential environmental influences for humpback dolphins in the Western Indian Ocean. We analyzed mitochondrial DNA data from 94 dolphins from the coasts of South Africa, Mozambique, Tanzania and Oman, employing frequency-based and maximum-likelihood algorithms to assess population structure and migration patterns. The genetic data were combined with 13 years of remote sensing oceanographic data of variables known to influence cetacean dispersal and population structure. Our analyses show strong and highly significant genetic structure between all putative populations, except for those in South Africa and Mozambique. Interestingly, the oceanographic data display marked environmental heterogeneity between all sampling areas and a degree of overlap between South Africa and Mozambique. Our combined analyses therefore suggest the occurrence of genetically isolated populations of humpback dolphins in areas that are environmentally distinct. This study highlights the utility of molecular tools in combination with high-resolution and high-coverage environmental data to address questions not only pertaining to genetic population structure, but also to relevant ecological processes in marine species.
Member of
ISSN
0018-067X
Resource URL
Category
Journal articles