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Hun, Avar and conquering Hungarian nomadic groups arrived to the Carpathian Basin from the Eurasian Steppes and significantly influenced its political and ethnical landscape, however their origin remains largely unknown. In order to shed light on the genetic affinity of above groups we have determined Y chromosomal haplogroups and autosomal loci, suitable to predict biogeographic ancestry, from 49 individuals, supposed to represent the power/military elit. Haplogroups from the Hun-age are consistent with Xiongnu ancestry of European Huns. Most of the Avar-age individuals carry east Eurasian Y haplogroups typical for modern north-eastern Siberian and Buryat populations and their autosomal loci indicate mostly un-admixed Asian characteristics. In contrast the conquering Hungarians seem to be a recently assembled population incorporating un-admixed European, Asian as well as admixed components. Their heterogeneous paternal and maternal lineages indicate similar supposed phylogeographic origin of males and females, derived from Central-Inner Asian and European Pontic Steppe sources.

Hun, Avar and conquering Hungarian nomadic groups arrived to the Carpathian Basin from the Eurasian Steppes and significantly influenced its political and ethnical landscape, however their origin remains largely unknown. In order to shed light on the genetic affinity of above groups we have determined Y chromosomal haplogroups and autosomal loci, suitable to predict biogeographic ancestry, from 49 individuals, supposed to represent the power/military elit. Haplogroups from the Hun-age are consistent with Xiongnu ancestry of European Huns. Most of the Avar-age individuals carry east Eurasian Y haplogroups typical for modern north-eastern Siberian and Buryat populations and their autosomal loci indicate mostly un-admixed Asian characteristics. In contrast the conquering Hungarians seem to be a recently assembled population incorporating un-admixed European, Asian as well as admixed components. Their heterogeneous paternal and maternal lineages indicate similar supposed phylogeographic origin of males and females, derived from Central-Inner Asian and European Pontic Steppe sources.

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long-term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long-term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifi- cally, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long-term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1-2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large dedines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long-term dynamics of body size. The long-term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long-term data sets on dreissenid populations, although dearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support. ; Deutsche Forschungsgemeinschaft (DFG) [JE 288/8-1]; G.E. Hutchinson Chair at the Cary Institute of Ecosystem Studies (DLS); NSF-LTREB grants [DEB-1556246]; NSF-OPUS grant [DEB-1456532]; DFG [JE 288/9-1, JE 288/9-2]; USGS [G14AC000263]; US EPA [GL00E01184]; Cornell Agricultural Experiment Station [NYC-0226747]; New York State Department of Environmental Conservation grants; NSF [1517823]; Belarusian Republican Foundation for Fundamental Research; Mercator Fellowship; [TaMOP-4.2.2.A-11/1/KONV-2012-0038]; [GINOP-2.3.2-15-2016-00019] ; This study is a contribution of the Invasion Dynamics Network (InDyNet), funded by the Deutsche Forschungsgemeinschaft (DFG; JE 288/8-1) including a Mercator Fellowship to DLS. Additional support came from the G.E. Hutchinson Chair at the Cary Institute of Ecosystem Studies (DLS), NSF-LTREB grants (most recently DEB-1556246), and NSF-OPUS grant DEB-1456532 to DLS; DFG projects JE 288/9-1 and JE 288/9-2 to JMJ; TaMOP-4.2.2.A-11/1/KONV-2012-0038 and the GINOP-2.3.2-15-2016-00019 to CSB and LG-T; USGS G14AC000263 and US EPA GL00E01184 to LEB and AYK; Cornell Agricultural Experiment Station NYC-0226747 and New York State Department of Environmental Conservation grants to LGR and ALH, and NSF grant 1517823 (ALH); and the Belarusian Republican Foundation for Fundamental Research to BA and OM. We thank Krzysztof Lewandowski for his help with data from Polish lakes; Mike Davis, the Minnesota Department of Natural Resources, and the United States Army Corps of Engineers for the Lake Pepin data; Kristen Holeck and Ed Mills for help with Oneida Lake data; the Onondaga County Department of Water Environment Protection; Ulrike Scharfenberger for her advice on the statistical analyses; Jaclyn McGuire for helping to gather information for the supplementary materials; Maggie Oudsema; and Juergen Geist, other InDyNet members, and Ladd Johnson, Alex Latzka, and Teresa Newton for helpful comments and suggestions. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.