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      Population Structure of Humpback Whales from Their Breeding Grounds in the South Atlantic and Indian Oceans

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          Although humpback whales are among the best-studied of the large whales, population boundaries in the Southern Hemisphere (SH) have remained largely untested. We assess population structure of SH humpback whales using 1,527 samples collected from whales at fourteen sampling sites within the Southwestern and Southeastern Atlantic, the Southwestern Indian Ocean, and Northern Indian Ocean (Breeding Stocks A, B, C and X, respectively). Evaluation of mtDNA population structure and migration rates was carried out under different statistical frameworks. Using all genetic evidence, the results suggest significant degrees of population structure between all ocean basins, with the Southwestern and Northern Indian Ocean most differentiated from each other. Effective migration rates were highest between the Southeastern Atlantic and the Southwestern Indian Ocean, followed by rates within the Southeastern Atlantic, and the lowest between the Southwestern and Northern Indian Ocean. At finer scales, very low gene flow was detected between the two neighbouring sub-regions in the Southeastern Atlantic, compared to high gene flow for whales within the Southwestern Indian Ocean. Our genetic results support the current management designations proposed by the International Whaling Commission of Breeding Stocks A, B, C, and X as four strongly structured populations. The population structure patterns found in this study are likely to have been influenced by a combination of long-term maternally directed fidelity of migratory destinations, along with other ecological and oceanographic features in the region.

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          Most cited references 17

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          Arlequin (version 3.0): An integrated software package for population genetics data analysis

          Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on
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            DnaSP, DNA polymorphism analyses by the coalescent and other methods.

            DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. The software package, including complete documentation and examples, is freely available to academic users from:
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              Identification of management units using population genetic data.

              The identification of management units (MUs) is central to the management of natural populations and is crucial for monitoring the effects of human activity upon species abundance. Here, we propose that the identification of MUs from population genetic data should be based upon the amount of genetic divergence at which populations become demographically independent instead of the current criterion that focuses on rejecting panmixia. MU status should only be assigned when the observed estimate of genetic divergence is significantly greater than a predefined threshold value. We emphasize the need for a demographic interpretation of estimates of genetic divergence given that it is often the dispersal rate of individuals that is the parameter of immediate interest to conservationists rather than the historical amount of gene flow.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                8 October 2009
                : 4
                : 10
                [1 ]Cetacean Conservation and Research Program, Global Conservation-Marine, Wildlife Conservation Society, Bronx, New York, United States of America
                [2 ]Sackler Institute for Comparative Genomics and Conservation Genetics Program, American Museum of Natural History, New York, New York, United States of America
                [3 ]American Museum of Natural History, Center for Biodiversity and Conservation, New York, New York, United States of America
                [4 ]Department of E3B, Columbia University, New York, New York, United States of America
                [5 ]University of Pretoria, Mammal Research Institute, Pretoria, Cape Town, South Africa
                [6 ]Environment Society of Oman, Ruwi, Muscat, Sultanate of Oman
                [7 ]Instituto Baleia Jubarte, Caravelas, Bahia, Brazil
                [8 ]Oceanography Department, University of Cape Town, Rondebosch, South Africa
                [9 ]Marine and Coastal Management, Rogge Bay, South Africa
                [10 ]Faculdade de Biociências, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
                [11 ]Wildlife Conservation Society-Madagascar Country Program, Antananarivo, Madagascar
                [12 ]Agence Nationale des Parcs Nationaux, Ministère du Tourisme et des Parcs Nationaux, Libreville, Gabon
                [13 ]Association Megaptera, Paris, France
                [14 ]Université de La Rochelle, LIENSS, Institut du Littoral et de l'Environnement, La Rochelle, France
                American Museum of Natural History, United States of America
                Author notes

                Conceived and designed the experiments: HR CP MM MSL PBB KPF GM PJE TC MHE SLB DPGHK MM JB MT YR SN MV JK. Performed the experiments: HR CP MM MSL PBB KPF GM PJE TC MHE SLB DPGHK MM JB MT YR SN MV JK. Analyzed the data: HR CP MM MSL. Contributed reagents/materials/analysis tools: HR CP MM MSL PBB KPF GM PJE TC MHE SLB DPGHK MM JB MT YR SN MV JK. Wrote the paper: HR CP MM MSL. Drafting the article or revising it critically for important intellectual content: CP MM MSL PBB KPF GM PJE TC MHE SLB DPGHK MM JB MT YR SN MV JK. Final approval of the version to be published: CP MM MSL PBB KPF GM PJE TC MHE SLB DPGHK MM JB MT YR SN MV JK.

                Rosenbaum et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 11
                Research Article
                Evolutionary Biology/Evolutionary Ecology
                Genetics and Genomics/Population Genetics
                Marine and Aquatic Sciences/Biological Oceanography
                Marine and Aquatic Sciences/Conservation Science
                Marine and Aquatic Sciences/Genetics, Genomics, and Barcoding



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