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The global warming potential of nitrous oxide (N2O) and its long atmospheric lifetime mean its presence in the atmosphere is of major concern, and that methods are required to measure and reduce emissions. Large spatial and temporal variations means, however, that simple extrapolation of measured data is inappropriate, and that other methods of quantification are required. Although process-based models have been developed to simulate these emissions, they often require a large amount of input data that is not available at a regional scale, making regional and global emission estimates difficult to achieve. The spatial extent of organic soils means that quantification of emissions from these soil types is also required, but will not be achievable using a process-based model that has not been developed to simulate soil water contents above field capacity or organic soils. The ECOSSE model was developed to overcome these limitations, and with a requirement for only input data that is readily available at a regional scale, it can be used to quantify regional emissions and directly inform land-use change decisions. ECOSSE includes the major processes of nitrogen (N) turnover, with material being exchanged between pools of SOM at rates modified by temperature, soil moisture, soil pH and crop cover. Evaluation of its performance at site-scale is presented to demonstrate its ability to adequately simulate soil N contents and N2O emissions from cropland soils in Europe. Mitigation scenarios and sensitivity analyses are also presented to demonstrate how ECOSSE can be used to estimate the impact of future climate and land-use change on N2O emissions.
Permafrost degradation influences the morphology, biogeochemical cycling and hydrology of Arctic landscapes over a range of time scales. To reconstruct temporal patterns of early to late Holocene permafrost and thermokarst dynamics, site-specific palaeo-records are needed. Here we present a multi-proxy study of a 350-cm-long permafrost core from a drained lake basin on the northern Seward Peninsula, Alaska, revealing Lateglacial toHolocene thermokarst lake dynamics in a central location of Beringia. Use of radiocarbon dating, micropalaeontology (ostracods and testaceans), sedimentology (grain-size analyses, magnetic susceptibility, tephra analyses), geochemistry (total nitrogen and carbon, total organic carbon, C-13(org)) and stable water isotopes (O-18, D, dexcess) of ground ice allowed the reconstruction of several distinct thermokarst lake phases. These include a pre-lacustrine environment at the base of the core characterized by the Devil Mountain Maar tephra (22800 +/- 280cal. a BP, Unit A), which has vertically subsided in places due to subsequent development of a deep thermokarst lake that initiated around 11800cal. a BP (Unit B). At about 9000cal. a BP this lake transitioned from a stable depositional environment to a very dynamic lake system (Unit C) characterized by fluctuating lake levels, potentially intermediate wetland development, and expansion and erosion of shore deposits. Complete drainage of this lake occurred at 1060cal. a BP, including post-drainage sediment freezing from the top down to 154cm and gradual accumulation of terrestrial peat (Unit D), as well as uniform upward talik refreezing. This core-based reconstruction of multiple thermokarst lake generations since 11800cal. a BP improves our understanding of the temporal scales of thermokarst lake development from initiation to drainage, demonstrates complex landscape evolution in the ice-rich permafrost regions of Central Beringia during the Lateglacial and Holocene, and enhances our understanding of biogeochemical cycles in thermokarst-affected regions of the Arctic.
The transition from hunting and gathering to farming involved profound cultural and technological changes. In Western and Central Europe, these changes occurred rapidly and synchronously after the arrival of early farmers of Anatolian origin [1-3], who largely replaced the local Mesolithic hunter-gatherers [1, 4-6]. Further east, in the Baltic region, the transition was gradual, with little or no genetic input from incoming farmers [7]. Here we use ancient DNA to investigate the relationship between hunter-gatherers and farmers in the Lower Danube basin, a geographically intermediate area that is characterized by a rapid Neolithic transition but also by the presence of archaeological evidence that points to cultural exchange, and thus possible admixture, between hunter-gatherers and farmers. We recovered four human paleogenomes (1.13 to 4.13 coverage) from Romania spanning a time transect between 8.8 thousand years ago (kya) and 5.4 kya and supplemented them with two Mesolithic genomes (1.73- and 5.33) from Spain to provide further context on the genetic background of Mesolithic Europe. Our results show major Western hunter-gatherer (WHG) ancestry in a Romanian Eneolithic sample with a minor, but sizeable, contribution from Anatolian farmers, suggesting multiple admixture events between hunter-gatherers and farmers. Dietary stableisotope analysis of this sample suggests a mixed terrestrial/ aquatic diet. Our results provide support for complex interactions among hunter-gatherers and farmers in the Danube basin, demonstrating that in some regions, demic and cultural diffusion were not mutually exclusive, but merely the ends of a continuum for the process of Neolithization.
Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here, we present a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM, ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e., upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.
The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.
Effects of topographic smoothing on the simulation of winter precipitation in High Mountain Asia
(2017)
Numerous studies have projected future changes in High Mountain Asia water resources based on temperature and precipitation from global circulation models (GCMs) under future climate scenarios. Although the potential benefit of such studies is immense, coarse grid-scale GCMs are unable to resolve High Mountain Asia's complex topography and thus have a biased representation of regional weather and climate. This study investigates biases in the simulation of physical mechanisms that generate snowfall and contribute to snowpack in High Mountain Asia in coarse topography experiments using the Weather Research and Forecasting model. Regional snowpack is event driven, thus 33 extreme winter orographic precipitation events are simulated at fine atmospheric resolution with 6.67 km resolution topography and smoothed 1.85° × 1.25° GCM topography. As with many modified topography experiments performed in other regions, the distribution of precipitation is highly dependent on first-order orographic effects, which dominate regional meteorology. However, we demonstrate that topographic smoothing enhances circulation in simulated extratropical cyclones, with significant impacts on orographic precipitation. Despite precipitation reductions of 28% over the highest ranges, due to reduced ascent on windward slopes, total precipitation over the study domain increased by an average of 9% in smoothed topography experiments on account of intensified extratropical cyclone dynamics and cross-barrier moisture flux. These findings identify an important source of bias in coarse-resolution simulated precipitation in High Mountain Asia, with important implications for the application of GCMs toward projecting future hydroclimate in the region.
The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. Here we analyse a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (similar to 22x) and seven to similar to 1x coverage, to investigate the impact of these on Europe's genetic landscape. These data suggest genomic shifts with the advent of the Neolithic, Bronze and Iron Ages, with interleaved periods of genome stability. The earliest Neolithic context genome shows a European hunter-gatherer genetic signature and a restricted ancestral population size, suggesting direct contact between cultures after the arrival of the first farmers into Europe. The latest, Iron Age, sample reveals an eastern genomic influence concordant with introduced Steppe burial rites. We observe transition towards lighter pigmentation and surprisingly, no Neolithic presence of lactase persistence.
Thermokarst lake landscapes are permafrost regions, which are prone to rapid (on seasonal to decadal time scales) changes, affecting carbon and nitrogen cycles. However, there is a high degree of uncertainty related to the balance between carbon and nitrogen cycling and storage. We collected 12 permafrost soil cores from six drained thermokarst lake basins (DTLBs) along a chronosequence north of Teshekpuk Lake in northern Alaska and analyzed them for carbon and nitrogen contents. For comparison, we included three lacustrine cores from an adjacent thermokarst lake and one soil core from a non thermokarst affected remnant upland. This allowed to calculate the carbon and nitrogen stocks of the three primary landscape units (DTLB, lake, and upland), to reconstruct the landscape history, and to analyze the effect of thermokarst lake formation and drainage on carbon and nitrogen stocks. We show that carbon and nitrogen contents and the carbon-nitrogen ratio are considerably lower in sediments of extant lakes than in the DTLB or upland cores indicating degradation of carbon during thermokarst lake formation. However, we found similar amounts of total carbon and nitrogen stocks due to the higher density of lacustrine sediments caused by the lack of ground ice compared to DTLB sediments. In addition, the radiocarbon-based landscape chronology for the past 7,000years reveals five successive lake stages of partially, spatially overlapping DTLBs in the study region, reflecting the dynamic nature of ice-rich permafrost deposits. With this study, we highlight the importance to include these dynamic landscapes in future permafrost carbon feedback models. Plain Language Summary When permanently frozen soils (permafrost) contain ice-rich sediments, the thawing of this permafrost causes the surface to sink, which may result in lake formation. This process, the thaw of ice-rich permafrost and melting of ground ice leads to characteristic landforms-known as thermokarst. Once such a thaw process is initiated in ice-rich sediments, a thaw lake forms and grows by shoreline erosion, eventually expanding until a drainage pathway is encountered and the lake eventually drains, resulting in a drained thermokarst lake basin. In our study, we show that such a thermokarst-affected landscape north of Teshekpuk Lake in northern Alaska is shaped by repeated thaw lake formation and lake drainage events during the past 7,000years, highlighting the dynamic nature of these landscapes. These landscape-scale processes have a big effect on the carbon and nitrogen stored in permafrost soils. We show that large amounts of carbon (>45kg C/m(2)) and nitrogen (>2.6kg N/m(2)) are stored in unfrozen lake sediments and in frozen soil sediments. The findings are important when considering the potential effect that permafrost thaw has for the global climate through releasing carbon and nitrogen, which was frozen and therefore locked away for millennia, from the active carbon cycle.
In organic solar cells, the resulting device efficiency depends strongly on the local morphology and intermolecular interactions of the blend film. Optical spectroscopy was used to identify the spectral signatures of interacting chromophores in blend films of the donor polymer PM6 with two state-of-the-art nonfullerene acceptors, Y6 and N4, which differ merely in the branching point of the side chain. From temperature-dependent absorption and luminescence spectroscopy in solution, it is inferred that both acceptor materials form two types of aggregates that differ in their interaction energy. Y6 forms an aggregate with a predominant J-type character in solution, while for N4 molecules the interaction is predominantly in a H-like manner in solution and freshly spin-cast film, yet the molecules reorient with respect to each other with time or thermal annealing to adopt a more J-type interaction. The different aggregation behavior of the acceptor materials is also reflected in the blend films and accounts for the different solar cell efficiencies reported with the two blends.