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Horse domestication revolutionized warfare and accelerated travel, trade, and the geographic expansion of languages. Here, we present the largest DNA time series for a non-human organism to date, including genome-scale data from 149 ancient animals and 129 ancient genomes (>= 1-fold coverage), 87 of which are new. This extensive dataset allows us to assess the modem legacy of past equestrian civilisations. We find that two extinct horse lineages existed during early domestication, one at the far western (Iberia) and the other at the far eastern range (Siberia) of Eurasia. None of these contributed significantly to modern diversity. We show that the influence of Persian-related horse lineages increased following the Islamic conquests in Europe and Asia. Multiple alleles associated with elite-racing, including at the MSTN "speed gene," only rose in popularity within the last millennium. Finally, the development of modem breeding impacted genetic diversity more dramatically than the previous millennia of human management.
The existing optical microscopes form an image by collecting photons emitted from an object. Here we report on the experimental realization of microscopy without the need for direct optical communication with the sample. To achieve this, we have scanned a single gold nanoparticle acting as a nanoantenna in the near field of a sample and have studied the modification of its intrinsic radiative properties by monitoring its plasmon spectrum
This study follows up on a previous downscaling intercomparison for present climate. Using a larger set of eight methods the authors downscale atmospheric fields representing present (1981-2000) and future (2046-65) conditions, as simulated by six global climate models following three emission scenarios. Local extremes were studied at 20 locations in British Columbia as measured by the same set of 27 indices, ClimDEX, as in the precursor study. Present and future simulations give 2 x 3 x 6 x 8 x 20 x 27 = 155 520 index climatologies whose analysis in terms of mean change and variation is the purpose of this study. The mean change generally reinforces what is to be expected in a warmer climate: that extreme cold events become less frequent and extreme warm events become more frequent, and that there are signs of more frequent precipitation extremes. There is considerable variation, however, about this tendency, caused by the influence of scenario, climate model, downscaling method, and location. This is analyzed using standard statistical techniques such as analysis of variance and multidimensional scaling, along with an assessment of the influence of each modeling component on the overall variation of the simulated change. It is found that downscaling generally has the strongest influence, followed by climate model; location and scenario have only a minor influence. The influence of downscaling could be traced back in part to various issues related to the methods, such as the quality of simulated variability or the dependence on predictors. Using only methods validated in the precursor study considerably reduced the influence of downscaling, underpinning the general need for method verification.