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Stewart, J. R.

Publications and source records attributed to Stewart, J. R..

3 recordsLinked to original sources

Long-term hunter-gatherer continuity in the Rhine-Meuse region was disrupted by local formation of expansive Bell Beaker groups

The first phase of the ancient DNA revolution painted a broad-brush picture of European Holocene prehistory, whereby 6500-4000 BCE, farmers descending from western Anatolians mixed with local hunter-gatherers resulting in 70-100% ancestry turnover, then 3000-2500 BCE people associated with the Corded Ware complex spread steppe ancestry into north-central Europe. We document an exception to this pattern in the wider Rhine-Meuse area in communities in the wetlands, riverine areas, and coastal areas of the western and central Netherlands, Belgium and western Germany, where we assembled genome-wide data for 109 people 8500-1700 BCE. Here, a distinctive population with high hunter-gatherer ancestry ([~]50%) persisted up to three thousand years later than in continental European regions, reflecting limited incorporation of females of Early European Farmer ancestry into local communities. In the western Netherlands, the arrival of the Corded Ware complex was also exceptional: lowland individuals from settlements adopting Corded Ware pottery had hardly any steppe ancestry, despite a characteristic early Corded Ware Y-chromosome. The limited influx may reflect the unique ecology of the regions river-dominated landscapes, which were not amenable to wholesale adoption of the early Neolithic type of farming introduced by Linearbandkeramik, making it possible for previously established groups to thrive, and creating a persistent but permeable boundary that allowed transfer of ideas and low-level gene flow. This changed with the formation-through-mixture of Bell Beaker using populations [~]2500 BCE by fusion of local Rhine-Meuse people (9-17%) and Corded Ware associated migrants of both sexes. Their expansion from the Rhine-Meuse region then had a disruptive impact across a much wider part of northwest Europe, including Britain where its arrival was the main source of a 90-100% replacement of local Neolithic peoples.

genomics↗

Ancient DNA reveals interstadials as a driver of the common vole population dynamics during the last glacial period

1AimThe common vole is a temperate rodent widespread across Europe. It was also one of the most abundant small mammal species throughout the Late Pleistocene. Phylogeographic studies of its extant populations suggested the Last Glacial Maximum (LGM, 26.5-19 ka ago) as one of the main drivers of the species population dynamics. However, analyses based solely on extant genetic diversity may not recover the full complexity of past population history. The main aim of this study was to investigate the evolutionary history and identify the main drivers of the common vole population dynamics during the Late Pleistocene. LocationEurope TaxonCommon vole (Microtus arvalis) MethodsWe generated a dataset comprising 4.2 kb-long fragment of mitochondrial DNA from 148 ancient and 51 modern specimens sampled from multiple localities across Europe and covering the last 60 thousand years (ka). We used Bayesian inference to reconstruct their phylogenetic relationships and to estimate the age of specimens that were not directly dated. ResultsWe estimate the time to the most recent common ancestor of all Last Glacial and extant common vole lineages to 90 ka ago and the divergence of the main mtDNA lineages present in extant populations to between 55 and 40 ka ago, earlier than previous estimates. We find multiple lineage turnovers in Europe in the period of high climate variability at the end of Marine Isotope Stage 3 (MIS 3; 57-29 ka ago) in addition to those found previously around the Pleistocene/Holocene transition. Conversely, data from the Western Carpathians suggest continuity throughout the LGM even at high latitudes. Main conclusionsOur results suggest that the main factor affecting the common vole populations during the last glacial period was the reduction of open habitats during the interstadial periods while the climate deterioration during the LGM had little impact on species population dynamics.

evolutionary biology↗

Bayesian analysis of source tracking markers to estimate the effects of an urban sanitation intervention on human fecal contamination in Mozambique

Fecal source tracking (FST) may be useful to assess pathways of fecal contamination in domestic environments and to estimate the impacts of water, sanitation, and hygiene (WASH) interventions in low-income settings. We measured two non-specific and two human-associated fecal indicators in water, soil, and surfaces before and after a shared latrine intervention from low-income households in Maputo, Mozambique participating in the Maputo Sanitation (MapSan) trial. Up to a quarter of households were impacted by human fecal contamination, but trends were unaffected by improvements to shared sanitation facilities. The intervention reduced E. coli gene concentrations in soil but did not impact culturable E. coli or the prevalence of human FST markers in a difference-in-differences analysis. Using a novel Bayesian hierarchical modeling approach to account for human marker diagnostic sensitivity and specificity, we revealed a high amount of uncertainty associated with human FST measurements and intervention effect estimates. The field of microbial source tracking would benefit from adding measures of diagnostic accuracy to better interpret findings, particularly when FST analyses convey insufficient information for robust inference. With improved measures, FST could help identify dominant pathways of human and animal fecal contamination in communities and guide implementation of effective interventions to safeguard health. SYNOPSISAn urban sanitation intervention had minimal and highly uncertain effects on human fecal contamination after accounting for fecal indicator sensitivity and specificity. TOC GRAPHIC/ABSTRACT ART O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/432000v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@312d2dorg.highwire.dtl.DTLVardef@8cf2caorg.highwire.dtl.DTLVardef@197b549org.highwire.dtl.DTLVardef@fefeb3_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗