Our explorative MDS analysis again indicates mixed ancestries related 
to the Scandinavian EIA, with regional differences that point to varied 
local admixture (Fig. 4e and Extended Data Fig. 10).
In Britain, most of the individuals recovered from the two late Viking 
Age mass graves identified at Ridgeway Hill, Dorset, and St John’s 
College, Oxford6, show ancestries typical of those seen in Viking Age 
southern Scandinavia (Fig. 4f). Further west, North Atlantic Viking Age 
individuals in the Faroe Islands, Iceland and Greenland carry ancestry 
from the Scandinavian Peninsula, with several individuals showing the 
continental central Europe-related ancestry signal found in south -
ern Scandinavia (Fig. 4f ) and others who share substantial ancestry 
with Iron Age Britain. In contrast to previous hypotheses68, we found 
a marginal enrichment of ancestry related to Britain and Ireland in 
men (15 out of 17 men and 3 out of 6 women with at least one accepted 
model involving Iron or Roman Age Britain as source; Fisher’s exact 
test P = 0.089) (Extended Data Fig. 7c,e). However, sampling of addi-
tional individuals to improve distinction between early English- and 
Norse-related ancestries would be required to fully test this hypothesis.
In eastern Europe, we observe EIA Scandinavian ancestries in a Viking 
Age burial from Ukraine, and these ancestries are overrepresented 
in Viking Age burials from present-day Russia. At Staraya Ladoga in 
western Russia, we observe several individuals with EIA Scandinavian 
Peninsula-related ancestry and at least one individual dated to the 
eleventh century with apparent ancestry related to Iron Age Britain. 
The relative absence of Iron Age central European ancestry, which was 
largely restricted to southern Scandinavia during the Viking Age, is thus 
indicative that these individuals may have originated in the central/
northern parts of Sweden or Norway, where Viking Age individuals 
show the most similar ancestry profiles to them.
Conclusions
Our approach, Twigstats, transfers the power advantage of haplotype- 
based approaches to a fully temporal framework, which is applica -
ble to f-statistics and enables previously unavailable unbiased and 
time-stratified analyses of admixture. We demonstrated that Twigstats 
enables fine-scale quantitative modelling of ancestry proportions, 
revealing wide-ranging ancestry changes that affect northern and  
central Europe during the Iron, Roman and Viking ages. We reveal evi-
dence of the southward and/or eastward expansion of individuals who 
probably spoke Germanic languages and who had Scandinavian-related 
ancestry in the first half of the first millennium ce. We note that 
‘Scandinavian-related’ in this context relates to the ancient genomes 
available, and so it is entirely possible that these processes were driven, 
for example, from regions in northern-central Europe. This could be 
consistent with the attraction of the greater wealth, which tended to 
build up among Rome’s immediate neighbours and may have played 
a major role in vectors of migration internal to communities in Europe 
who lived beyond the Roman frontier52. Later, patterns of gene flow 
seem to have turned northwards, with the spread of Iron Age Central 
Europe-related ancestry into Scandinavia. Overall, our approach can 
be used for the reconstruction of new high-resolution genetic histories 
around the world.
Online content
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ries, source data, extended data, supplementary information, acknowl-
edgements, peer review information; details of author contributions 
and competing interests; and statements of data and code availability 
are available at https://doi.org/10.1038/s41586-024-08275-2.
1. Lawson, D. J., Hellenthal, G., Myers, S. & Falush, D. Inference of population structure using 
dense haplotype data. PLoS Genet. 8, 11–17 (2012).