As species recover from exploitation, continued assessments of connectivity and population structure are warranted to provide information for conservation and management. This is particularly true in species with high dispersal capacity, such as migratory whales, where patterns of connectivity could change rapidly. Here we build on a previous long-term, large-scale collaboration on southern right whales (Eubalaena australis) to combine new (nnew) and published (npub) mitochondrial (mtDNA) and microsatellite genetic data from all major wintering grounds and, uniquely, the South Georgia (Islas Georgias del Sur: SG) feeding grounds. Specifically, we include data from Argentina (npub mtDNA/microsatellite = 208/46), Brazil (nnew mtDNA/microsatellite = 50/50), South Africa (nnew mtDNA/microsatellite = 66/77, npub mtDNA/microsatellite = 350/47), Chile–Peru (nnew mtDNA/microsatellite = 1/1), the Indo-Pacific (npub mtDNA/microsatellite = 769/126), and SG (npub mtDNA/microsatellite = 8/0, nnew mtDNA/microsatellite = 3/11) to investigate the position of previously unstudied habitats in the migratory network: Brazil, SG, and Chile–Peru. These new genetic data show connectivity between Brazil and Argentina, exemplified by weak genetic differentiation and the movement of 1 genetically identified individual between the South American grounds. The single sample from Chile–Peru had an mtDNA haplotype previously only observed in the Indo-Pacific and had a nuclear genotype that appeared admixed between the Indo-Pacific and South Atlantic, based on genetic clustering and assignment algorithms. The SG samples were clearly South Atlantic and were more similar to the South American than the South African wintering grounds. This study highlights how international collaborations are critical to provide context for emerging or recovering regions, like the SG feeding ground, as well as those that remain critically endangered, such as Chile–Peru.

Collection and laboratory methods described in publication. Data archived here described as follows.

1. Microsatellite data

The repository contains microsatellite genotypes for all samples used in the analysis in genepop format: SRW_All_Data_SamplingLocationGenepop.txt

The order of populations in this file is as follows:

South Africa (n = 123)

Argentina (n = 46)

Brazil (n = 50)

South Georgia (n = 11)

Chile (n = 1)

Australia (n = 78)

New Zealand (n = 51)

As per Table 1 in the original manuscript.

2. Mitochondrial DNA data

This repository contains the mtDNA data in two formats:

(1) excel spreadsheet with haplotype names, genbank accession numbers, references and accession numbers, with count of each haplotype per sampling location: Dryad_mtDNA_Hap_Frequencies.xlsx

(2) Arlequin file linking haplotype counts and sequences in one file: 380bp_SGSRW_SouthAtlantic_Aug19.txt

The Indo-Pacific (Australia/New Zealand) dataset comes from original publication Carroll et al 2015

The Argentina and part of the South Africna dataset comes from original publication Carroll et al 2019