The Stanford researchers used recently developed software called ''Serial SimCoal'' to simulate genetic data based on different population scenarios, such as small (25,000 females) or large (300,000 females) populations of constant size, an expanding population, and scenarios involving migration and selection. Despite the range of scenarios created, the scientists could not find a match between the observed archaeological data and the simulations.
Christian Anderson, a former Stanford undergraduate, developed the software while working with Elizabeth Hadly, associate professor of biological sciences. She has used the approach to analyze the ancient DNA of small mammals. ''I believe it's the first time it has been used to analyze ancient human DNA,'' Mountain said. ''It's computationally intensive and requires DNA data from many individuals.''
The finding is important because it questions the common assumption that residents of a particular place are descendants of its earlier inhabitants, Mountain said. ''Also, it raises a number of other questions-what happened to the Etruscans?'' she said. ''It's stimulating for archaeologists and other social scientists to look into what might have been the causes of this decline in the population. It may have been quite abrupt. Mostly, it's a matter of guessing.''
According to Mountain, the field of anthropological genetics is replete with such educated guesses. ''There's so much storytelling that goes on in our field where people will see a particular genetic sequence and go, 'Aha! That means these people moved here and there,''' she said. ''I tend to be fairly skeptical and say, 'That's a nice story.' Before [this study] you could tell a number of stories consistent with the data. What we've done is narrowed down these stories, which for me is a really great leap forward.''