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236 results for “Eurasia”
Text-fig. 16. Upper part of the Botchi thin-bedded plant-bearing tuffaceous beds. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 16. Upper part of the Botchi thin-bedded plant-bearing tuffaceous beds.
Text-fig. 14. Dembi plant-bearing strata (4 km to the south of the Dembi Bay). in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 14. Dembi plant-bearing strata (4 km to the south of the Dembi Bay).
Text-fig. 9. Lower part of a fossil woody stem in the tuffaceous beds at Siziman. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 9. Lower part of a fossil woody stem in the tuffaceous beds at Siziman.
Text-fig. 15. Detail of the Dembi site. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 15. Detail of the Dembi site.
Data for: Elevational changes in insect herbivory on woody plants in six mountain ranges of temperate Eurasia: Sources of variation
<p>Current theory predicts that the intensity of biotic interactions, and particularly herbivory, decreases with increasing latitude and elevation. However, recent studies have revealed substantial variation in both the latitudinal and elevational patterns of herbivory. This variation is often attributed to differences in study design and type of data collected by different researchers. Here, we used a standardised sampling protocol along elevational gradients in six mountain ranges, located at different latitudes within temperate Eurasia, to uncover the sources of variation in elevational patterns in insect herbivory on woody plant leaves. We discovered the considerable variation in elevational patterns among different mountain ranges; nevertheless, herbivory generally decreased with increasing elevation at both the community-wide and individual plant species levels. This decrease was mostly due to openly living defoliators, whereas no significant association was detected between herbivory and elevation among insects living within plant tissues (i.e. miners and gallers). The elevational decrease in herbivory was significant for deciduous plants but not for evergreen plants, and for low-stature plants but not for tall plants. The community-wide herbivory increased with increases in both specific leaf area and leaf size. The strength of the negative correlation between herbivory and elevation increased from lower to higher latitudes. We conclude that elevational gradients in herbivory demonstrate considerable variation, and that this variation is mostly associated with herbivore feeding habit, some plant traits and latitude of the mountain range.</p>
Data for "Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multidecadal trend in the Warm Arctic Cold Eurasia pattern"
<p>Here the model experiment data used to create the figures in the article "Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern" are provided.</p>
Eurasia-fixed GNSS-derived velocity field for Turkey
<p>The dataset and the analysis is described in the <a href="http://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1844&context=earth">paper</a> and presented <a href="https://meetingorganizer.copernicus.org/EGU23/EGU23-12258.html">here</a>. The data fields are: longitude, latitude, E velocity, N velocity, sigma E, sigma N, rho, U velocity, sigma U, station. You can use the following code snippet to load your data to python:</p> <pre><code class="language-python">fields = ['longitude', 'latitude', 've', 'vn', 'se', 'sn', 'rho', 'vu', 'su', 'station'] df = pd.read_csv('Kurt_etal_2023.csv', header=None, names=fields)</code></pre> <p> </p>
Beyond 'greening' and 'browning': trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation
<p class="MsoNormal">Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long‑term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modelling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002–2020 time series and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally-uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non‑photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote‑sensing‑based monitoring of trends in grasslands so that underlying processes can be discerned.</p>
Supporting data for "Population Genomics of Postglacial Western Eurasia"
<p>This repository contains supplemental data from Allentoft, Sikora et al. "Population Genomics of Postglacial Western Eurasia". The following files are included</p> <p>supplementary_figures/</p> <p>Hi-res versions of supplementary figures </p> <p>ibd/</p> <p>Aggregate total IBD sharing rates between pairs of individuals in the full dataset. Includes auxiliary metadata files to use for IBD-based mixture models (code available at <a href="https://github.com/martinsikora/mixmodel_ibd">https://github.com/martinsikora/mixmodel_ibd</a>)</p> <p>For additional details on data generation, curation and sample metadata please consult the main paper.</p>
Data from: India-Eurasia convergence speed-up by passive-margin sediment subduction
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Data from: Declining human pressure and opportunities for rewilding in the steppes of Eurasia
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Data from: Ongoing India-Eurasia collision predominantly driven by Sumatra-Java slab pull
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Beyond ‘greening’ and ‘browning’: trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation
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Data for: Elevational changes in insect herbivory on woody plants in six mountain ranges of temperate Eurasia: Sources of variation
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Data from: Phylogenetic conservatism and biogeographic affinity influence woody plant species richness-climate relationships in eastern Eurasia
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Reconstructing the phylogeny and evolutionary history of freshwater fishes (Nemacheilidae) across Eurasia since early Eocene
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The role of fire in the carbon dynamics of the boreal forest II. - Eurasia model simulations of historical fire disturbance and carbon dynamics (1000-2002).
The boreal forest contains large reserves of carbon, and across this region wildfire is a common occurrence. To improve the understanding of how wildfire influences the carbon dynamics of this region, methods were developed to incorporate the spatial and temporal effects of fire into the Terrestrial ecosystem Model (TEM). The historical role of fire on carbon dynamics of the boreal region was evaluated within the context of ecosystem responses to changing atmospheric CO2 and climate. These results show that the role of historical fire on boreal carbon dynamics resulted in a net carbon sink; however, fire plays a major role in the interannual and decadal scale variation of source/sink relationships. To estimate the effects of future fire on boreal carbondynamics, spatially and temporally explicit empirical relationships between climate andfire were quantified. Fuel moisture, monthly severity rating, and air temperature explained a significant proportion of observed variability in annual area burned. These relationships were used to estimate annual area burned for future scenarios of climate change and were coupled to TEM to evaluate the role of future fire on the carbon dynamics of the North American boreal region for the 21st Century. Simulations with TEM indicate that boreal North America is a carbon sink in response to CO2 fertilization, climate variability, and fire, but an increase in fire leads to a decrease in the sink strength. While this study highlights the importance of fire on carbon dynamics in the boreal region, there are uncertainties in the effects of fire in TEM simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. Future studies should incorporate the role of dynamic vegetation to more accurately represent post-fire successional pr
House mouse Mus musculus dispersal in East Eurasia inferred from 98 newly determined complete mitochondrial genome sequences
<div> <p><span><span><span><span><span><span><span><span><span><span><span>The Eurasianhouse mouse <i>Mus musculus</i>is useful for tracing prehistorical human movement related to the spread of farming. We determined whole mitochondrial DNA (mtDNA) sequences (ca. 16,000 bp) of 98 wild-derived individuals of two subspecies, <i>M</i>. <i>m</i>. <i>musculus </i>(MUS) and <i>M</i>. <i>m</i>. <i>castaneus </i>(CAS). We revealed directional dispersals reaching as far asthe Japanese Archipelagofrom their homelands. Our phylogenetic analysis indicated that the eastward movement of MUS was characterised by five step-wise regional extension events: 1) broad spatial expansion into eastern Europe and the western part of western China, 2) dispersal to the eastern part of western China, 3) dispersal tonorthern China, 4) dispersal to the Korean Peninsula and 5) colonisation and expansion in the Japanese Archipelago. These events were estimated to have occurred during the last 2,000–18,000 years. The dispersal of CAS was characterised by three events: initial divergences(ca. 7,000–9,000 years ago) of haplogroups in northern most China and the eastern coast of India, followed by two population expansion events that likely originated from the Yangtze River basinto broad areas of South and Southeast Asia, including Sri Lanka, Bangladesh and Indonesia (ca. 4,000–6,000 years ago) and to Yunnan, southern China and the Japanese Archipelago (ca. 2,000–3,500). This study provides a solid framework for the spatiotemporal movementof the human-associated organisms in Holocene Eastern Eurasia using whole mtDNA sequences, reliable evolutionary rates and accurate branching patterns. The information obtained here contributes to the analysis of a variety of animals and plants associated with prehistoric human migration.</span></span></span></span></span></span></span></span></span></span></span></p> </div>
Data from: Genomic signature of successful colonization of Eurasia by the allopolyploid shepherd's purse (Capsella bursa-pastoris)
Polyploidization is a dominant feature of flowering plant evolution. However, detailed genomic analyses of the inter-population diversification of polyploids following genome duplication are still in their infancy, mainly because of methodological limits, both in terms of sequencing and computational analyses. The shepherd's purse (Capsella bursa-pastoris) is one of the most common weed species in the world. It is highly self-fertilizing, and recent genomic data indicate that it is an allopolyploid, resulting from hybridization between the ancestors of the diploid species Capsella grandiflora and Capsella orientalis. Here, we investigated the genomic diversity of C. bursa-pastoris, its population structure and demographic history, following allopolyploidization in Eurasia. To that end, we genotyped 261 C. bursa-pastoris accessions spread across Europe, the Middle East and Asia, using genotyping-by-sequencing, leading to a total of 4,274 SNPs after quality control. Bayesian clustering analyses revealed three distinct genetic clusters in Eurasia: one cluster grouping samples from Western Europe and Southeastern Siberia, the second one centered on Eastern Asia and the third one in the Middle East. Approximate Bayesian computation (ABC) supported the hypothesis that C. bursa-pastoris underwent a typical colonization history involving low gene flow among colonizing populations, likely starting from the Middle East towards Europe and followed by successive human-mediated expansions into Eastern Asia. Altogether, these findings bring new insights into the recent multistage colonization history of the allotetraploid C. bursa-pastoris and highlight ABC and genotyping-by-sequencing data as promising but still challenging tools to infer demographic histories of selfing allopolyploids.
Data from: Ancient trade routes shaped the genetic structure of horses in eastern Eurasia
Animal exchange networks have been shown to play an important role in determining gene flow among domestic animal populations. The Silk Road is one of the oldest continuous exchange networks in human history, yet its effectiveness in facilitating animal exchange across large geographic distances and topographically challenging landscapes has never been explicitly studied. Horses are known to have been traded along the Silk Roads; however, extensive movement of horses in connection with other human activities may have obscured the genetic signature of the Silk Roads. To investigate the role of the Silk Roads in shaping the genetic structure of horses in eastern Eurasia we analysed microsatellite genotyping data from 455 village horses sampled from 17 locations. Using least-cost path methods, we compared the performance of models containing the Silk Roads as corridors for gene flow with models containing single landscape features. We also determined whether the recent isolation of former Soviet Union countries from the rest of Eurasia has affected the genetic structure of our samples. The overall level of genetic differentiation was low, consistent with historically high levels of gene flow across the study region. The spatial genetic structure was characterised by a significant, albeit weak, pattern of isolation by distance across the continent with no evidence for the presence of distinct genetic clusters. Incorporating landscape features considerably improved the fit of the data; however, when we controlled for geographic distance, only the correlation between genetic differentiation and the Silk Roads remained significant, supporting the effectiveness of this ancient trade network in facilitating gene flow across large geographic distances in a topographically complex landscape.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.