 What I'm going to talk about is a small Dutch population, where everything is small in volume to per definition, called Oldenzaal and its development over time. Yes. So Oldenzaal is located on the eastern border of the Netherlands, almost in Germany. We are right here at the moment. Well, Oldenzaal was founded somewhere in the seventh or eighth century. We don't know the exact date of the foundation of this medieval town. We do know that the oldest dates of the burials that we have are from the starting of the seventh century. So what you see here is a map of Oldenzaal in the 16th century. You see in the middle a small church, and around this church there has always been a cemetery. And at this cemetery, not only people from the town of Oldenzaal were buried, but also people from the region around it. So the population that is buried there really is a regional population. So not just people from the city context, from an urban context, but also people from a rural context, which is both interesting and makes it even more complex. And at this cemetery, excavations took place until 2013. Not all the cemetery was excavated, but just parts of it, depending on what was going to be disturbed for all kinds of reconstruction plans. And as you can see, DNA samples were collected in the field already out of forensic conditions to avoid problems with contamination, which is, of course, a big issue with ancient DNA. So we planned on beforehand that we were going to do an extensive population analysis, which is quite interesting and has many benefits, because you can prepare, basically, yourself for what's going to come, so take specific precautions. And so the population research that we were going to do on these skeletons was basically a commercial project. So you can see that almost 3,000 skeletons were excavated, and 37% of them could be sampled in the field for DNA and isotopes by collecting teeth. So not everybody had teeth anymore, either due to disturbing activities in the cemetery, or people were simply old. They didn't have any teeth anymore. And from these almost 3,000 skeletons, we had to select 200. So we had a budget for 200, that's it. And within the budget, we defined several themes that we wanted to address, which is your basic demography. So by looking at sex and age distribution, we wanted to look at diet and health by means of carbon and nitrogen, isotopes, stature, and pathology, and migration and mobility also by addressing strontium and oxygen, isotopes, and DNA. And we wanted to view these themes from a diachronic perspective. So we know that this cemetery has been used from around 7th century until 1830. So we have over 1,000 years of burials. So you can really track this population over time and see what's happening. I'm a DNA specialist, so I did the DNA analysis. He's at Codecorp from the Free University of Amsterdam. Did the isotope analysis. And Ravel Panhuis, who is not in this session because he's overlapping, but he's around. So if you want to ask him, find him. He did the physical anthropology and paleo pathology. So this was really an integrated project from the beginning. Of course, spatial and temporal distribution are quite important in a project like this. What you see, the big blank gap in the middle is the church itself. And in gray, you see all the grays that were excavated. I think it's quite clear that especially in the south and the west, they are predominantly from the outer side of the cemetery. So typically the less favorite, the cheaper places. And that means that you already have a very strong selection of the population that you're going to analyze. You have a specific layer of the population, in this case predominantly the more lower layers of populations with the outer edges of the cemetery and, of course, the northern side. And to do this diapronic perspective, you need good dating. So we were looking specifically in areas with deep stratigraphy. So we could do Harris matrices because you can't see 14 dates every skeleton simply too costly. So you need to make sure that you get them from areas where you have different layers above each other and just assume that that represents a long period of time. So here you see the regions A to D, where we got our 200 skeletons from. If we zoom in on that, you can see that in the northern area, we mostly had people from the medieval period, so up to 1,500. And in the southern locations, more people from the post-medieval period. And the reason that we chose this division for the population is both practical because this enables also to compare it with other Dutch populations. It doesn't mean that this is the best division that you can make. But this is what we started with. And depending on your research question, of course, you can divide your population to different time periods. But for now, we chose this one. But still, we had 30 individuals that could not be dated, unfortunately. So quickly, for the data analysis for DNA, what do we do to answer our questions? For the autosomal DNA, we looked at the level of genetic variation. So how much variation do we have in this population? If you have a very low variation, it's an indication of a very close population. So like what we call inbreeding, so not much new DNA from outside getting into this population. And to see if we have population continuity or not, you want to compare the type of genetic variation between the different periods. Are they similar or not? And for the y-chromosomal and mitochondrial haplogroups, we now have a really cool, new way of modeling that and actually really look at population continuity. Because if you model for population continuity, you need to take mutation rate into consideration. You need to take population growth into consideration. Effective population size, which is the part of the population that actually does produce the next generation. And for the autosomal DNA, we do not have that kind of sophisticated models available yet. Unfortunately, but we do have that for the y-chromosomal and mitochondrial DNA. And for diet analysis, Lisette kind of made a reference database for the local population based on local zoo archaeological remains. And for migration, she refers to something that is not quite amazing. In my point of view, it's like a map with local bio-available strontium ratios for the Netherlands. And of course, if you want to know whether someone is local or not, you need to know what kind of strontium ratios are available in different regions in the world. And we don't have that for many regions yet. So having this really is a luxury. And for the oxygen ratio, she looked at the ISOIS database and modern available data. But because we had such a big population, we could also apply the statistical approach. So based on what is the average signal of our population and where do our outliers go? So for the results, basic demography, we saw that sex was equally divided over time, both in adults and non-adults, because in this case, we could also sex older children, which was quite new and interesting. We didn't see any changes over time. We didn't see any differences in the different areas of the cemeteries. It was quite a stable picture. We did see, however, that the age at death for the adults was relatively low compared to reference populations in both the Netherlands and elsewhere in Europe. We didn't see any significant changes over time. So this age at death stayed stable over time. What we did see, however, was a serious underrepresentation of non-adults and a rather unusual distribution of the age classes within the non-adults. So what you see here is adults versus non-adults in the medieval population and the post-medieval population. Over here, the medieval population, we have a bit over 30% children, which is on the low side but could be acceptable, could be really representative for what was going on. Then the post-medieval population, we have only 10% non-adults. And that's really not what you expect. Usually it's between 30% and 50%. So that either means that due to tephanomic processes, for example, children were less well-preserved and we simply didn't see them anymore. They were not there anymore. It could also mean that they were predominantly buried in a location that we simply didn't hit with the excavation. So that could also point to specific use of the spatial area of the cemetery and burial traditions. If you look at the age distribution within these non-adults in yellow, the medieval population in green, the post-medieval population, you see that the youngest age group, 0 to 5 years, is relatively underrepresented. Usually that is the largest age class. And so even there is something strange is going on. If we don't have a clear explanation for that at the moment, hopefully later we can answer this question. Concerning health, the stature of the population of the females and males was quite average concerning reference populations. We saw relatively low prevalence of cariose, but relatively high prevalence of fractures, peripheral and vertebral osteoarthritis, periodostitis and osteomalacy. We didn't find any clear evidence of tuberculosis, syphilis and leprosy, which is, I think, remarkable on such a large population. In terms of diachronic perspective, we saw the decrease of regular and seasonal enamel hypoplasia, but an increase of dental carias and antemortem tooth loss. So that might point to a change in diet over time. When we compare the sexes, we see that males have more fractures and more chronic sinusitis than females. It might point to a bit harsher conditions, working more limb conditions for males compared to females. When we look at the diet, I'm not going to go into this plot. I don't have time for that. But we see that the diet is predominantly based on C3 plants and animal proteins. The component of fish was remarkably low. It was nearly absent. Still, if we compare the sexes, we see that the men had a little bit more fish in their diet than the females in the medieval population, otherwise didn't see any changes over time. And we did see a relatively high nitrogen value in the northern zone, which is not related to the carbon. And in this case, that might indicate to higher prevalence of disease and or lack of food and or water. For migration, we saw that at least 15% of the analyzed individuals could be seen as non-local because their strontium-oxygen ratios were outside of the regional bandwidth. But the majority of the known locals had ratios that were still compatible with other regions within the Netherlands. Nevertheless, we do see evidence for some individuals, most probably originating from the UK, Germany, and Eastern Europe. Now, when we look at the genetic parts, we see a very stable picture of genetic variety over time. The population does not get more variety over time. It's quite stable. But overall, it's a relatively high level of variety with 81%. And that means that it's a quite open population. So they're combined with the isotope results. It points more towards a high level of mobility, so regional mobility as opposed to long-distance migration. And when we compare the different periods, we see that based on the autosomal DNA, there is no significant differences. So again, a very stable picture. But when we do the population modeling for the Y-chromosomal hypergroups, it's the same. We cannot reject population continuity. But we might be able to reject population continuity for the mitochondrial DNA. It's a very subtle signal. And it's not backed up with the isotope results. We don't see any difference between the males and females. So we need to dive into what could be the cause of that. In conclusion, what we basically see is a population consisting of laborers, people that worked on their relatively harsh conditions, had to work hard. More regional mobility than long-distance migration. But overall, a very stable population. Nothing much spectacular seems to be happening here. The temporal difference that we do pick up point more to changes in lifestyle and life conditions than really changes in the population itself. We also picked up some very subtle spatial differences, which point to differences in socioeconomic position. And I guess, in the end, this picture more or less fits with the fact that we have our skeletons from the outer edges of the cemetery. And I guess this is a nice basis, like a first glimpse into what happens in a regular Dutch town. But the point is that we hardly have any reference data. So how spectacularly boring or exciting this is, I don't know yet. So we need to do way more, of course. I'd love to get more skeletons, because 200 seem like a lot. We're talking about a regional population and over 1,000 years of burial. So in the end, it's not that much, really. And of course, we have a very strict selection of the population. We're addressing only one part of the population. And I'd love to get more dates. So we get more skeletons for the diagronic perspective and also narrow down these time frames to pick up more subtle details. Compare with other regions within the Netherlands and Europe. And also move on to paleoepidemiology, pathogen analysis, selection. Well, I'd like to thank a lot of people for contributing to this project. And that's what I'm going to leave it at.