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Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2008
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2009
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2010
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2011
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2012
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2013
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2014
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2015
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of obervatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans.In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables.
Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2016
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of obervatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans.In support of these objectives, a new 32m tower was deployed in Pleistocene Park, about 20km south of North-East Science Station in Cherskii, Russia. This station is currently measuring fluxes of carbon dioxide, methane, water vapor and energy in addition to other meteorological variables. This station was shut down August 25, 2016.
Supplementary File: Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia's most popular social network VK
<p>Supplementary file and dataset for the paper "Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia’s most popular social network VK"</p>
Landscape classes of combinations of elevation, slope angle, and aspect, for the Ilirney Lake System Region, Chukotka, Russia
<p>The elevation was accessed for the area of interest in 90 m spatial resolution from the TanDEM-X 90 m digital elevation model (DEM) product (Krieger et al, 2013). Prior to spatial topographical parameters extraction, the DEM was resampled from the 90-m cell spacing to a 30-m resolution. The result was classified into 589 different possible combinations of elevation, slope angle, aspect. For the classification we used the possible combinations of elevation, slope, and aspect which were grouped into the following categories:</p> <p>Elevation:</p> <ul> <li>0-400 m</li> <li>400-450m</li> <li>450-500m</li> <li>500-600m</li> <li>600-650m</li> <li>650-700m</li> <li>700-1000m</li> <li>1000-1500m</li> </ul> <p>Slope:</p> <ul> <li>0-2°</li> <li>2-4°</li> <li>4-6°</li> <li>6-8°</li> <li>8-10°</li> <li>10-12°</li> <li>12-16°</li> <li>16-18°</li> <li>18-20°</li> <li>20-25°</li> <li>25-50°</li> </ul> <p>Aspect:</p> <ul> <li>0-45°</li> <li>45-90°</li> <li>90-135°</li> <li>135-180°</li> <li>180-225°</li> <li>225-270°</li> <li>270-315°</li> <li>315-360°</li> </ul> <p>Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 642010.1, 654910.1, 7462218, 7492908 m (xmin, xmax, ymin, ymax)</p>
Simulated total forest (larch) coverage aggregated over the vicinity of the Ilirney lake system region, Chukotka, Russia
<p>The model LAVESI (Kruse et al. 2016) was updated (Kruse 2023) and forced with historical and future climate forcing for 3 simulation repeats. This data set uses the data set of Kruse (2023) and applies a threshold of 0.68 km m<sup>-2</sup> to differentiate forested areas according to the 2018 field inventories (Shevtsova et al., 2021). In this data set the total forest cover was summed up and the percent of total available areas is presented for the three climate forcings RCP 2.6, 4.5 and 8.5 and each complemented with a hypothetical cooling scenario from year 2300 CE onwards. The data provided is from years 1800, 1860, 1900, 1990, 2000 and in 5-year steps until 3000 CE and presents the mean over the three repeats of the sum of AGB of the whole study region: extent: 640008.2, 649998.2, 7475006, 7494716 m (xmin, xmax, ymin, ymax).</p> <p>Format: csv, with headers 1-year, Year in CE, 2-average percent forests cover for the study region, 3-upper and 4-lower, is the minimum and maximum value of the three simulations, 5-RCP, is the RCP scenario, 6-Cooling, contains in case of the cooling scenario the string “Cooling”.</p>
Checklist of the moss of aquatic and riverside habitats of the Komi Republic (European North-East of Russia)
<p>Представленная информация о мхах водных и прибрежно-водных местообитаний Республики Коми является дополнением к статье Г.В. Железновой, Т.П. Шубиной, Б.Ю. Тетерюка «Анализ флоры мхов водных и прибрежно-водных местообитаний Республики Коми», принятой к публикации в журнале «Известия Коми НЦ УрО РАН» в 2019 г.</p> <p>Список включает 275 таксонов мхов из 103 родов и 37 семейств. Он составлен на основе фактического материала, хранящегося в гербарии Института биологии Коми научного центра Уральского отделения Российской академии наук (SYKO) (УНУ «Научный гербарий SYKO Института биологии Коми НЦ УрО РАН») и литературных сведений (Ruprecht, 1850; Zickendrath, 1895, 1900; Поле, 1915; Кильдюшевский, 1956; Куваев, 1970).</p> <p>Исследованиями были охвачены прибрежные и водные местообитания водотоков и озер Республики Коми. На равнинной территории сборы выполнены в пределах тундры (подзона южной тундры), лесотундры, тайги (подзоны северной и средней тайги), в горах – на Полярном, Приполярном и Северном Урале. Полевые бриологические исследования проводились с использованием маршрутного и стационарного методов.</p> <p>Объем семейств, родов и названия видов приведены в основном согласно списку мхов Восточной Европы и Северной Азии (Check-list…, 2006)</p> <p>The checklist provides information about mosses aquatic and riverside habitats of the Komi Republic. It is a supplement to the article by G. V. Zheleznova, T. P. Shubina, B. Yu. Teteryuk "Analysis of the moss flora of aquatic and riverside habitats of the Komi Republic (European North-East of Russia)", accepted for publication in the journal "Proceedings of the Komi Science Center URD RAS" in 2019.</p> <p>The checklist includes 275 moss taxa from 103 genera and 37 families. It is based on the samples preserved in the Herbarium of the Institute of Biology of the Komi Scientific Center of the Ural Branch of the Russian Academy of Sciences (SYKO) and literary data (Ruprecht, 1850; Zickendrath, 1895, 1900; Pole, 1915; Kildyushevsky, 1956; Kuvaev, 1970). The species names were given according to “Checklist of mosses of East Europe and North Asia” (2006).</p> <p>The mosses were collected in aquatic and riverside habitats of the mountains and plain territories of the Komi Republic. The research covered three parts of the Urals mountain range: the Polar Urals, the Subpolar Urals and the Northern Urals. The plain territory was covered within the southern tundra, forest tundra, northern taiga and middle taiga.</p>
National Checklists 2017: Russia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Russia collected using effechecka and geonames polygons
National Checklists 2019: Russia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Russia collected using effechecka and geonames polygons
Simulated spatially-explicit above ground biomass of forests (larch) in the vicinity of the Ilirney lake system region, Chukotka, Russia
<p>The model LAVESI (Kruse et al. 2016) was updated (Kruse 2023) and forced with historical and future climate forcing for 3 simulation repeats. The data set contains simulated larch above ground biomass (AGB, in kg m<sup>-2</sup>) for the three climate forcings RCP 2.6, 4.5 and 8.5 and each complemented with a hypothetical cooling scenario from year 2300 CE onwards. The data provided is from years 2020, 2050, 2100 and proceeding in 100-year steps until 3000 CE.</p> <p>Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 640008.2, 649998.2, 7475006, 7494716 m (xmin, xmax, ymin, ymax)</p>
The long term series of characteristics of floods that happened to 12 rivers in Finland and northern Russia.
<p>The dataset of flood’s characteristics (annual and spring): the volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date were estimated for each year from the daily series of water discharges observed at the hydrometric sites. To define the dates of spring flood begin and end we applied the semi-empirical method given in Shevnina (2013). The yearly maximum water discharges have been obtained in Gudmundsson et al. (2018) for the period until 2017; this dataset gives a good agreement in the estimations for the overlapping periods. The series of volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date are given in the dataset supplementing the study submitted to the Water resource research journal (<a href="https://agupubs.onlinelibrary.wiley.com/journal/19447973">https://agupubs.onlinelibrary.wiley.com/journal/19447973</a> ). </p> <p>The daily series of water river discharges at the sites located in Finland were extracted from (a) the Global runoff database <a href="https://portal.grdc.bafg.de/">https://portal.grdc.bafg.de/</a> (for the period from beginning of the observations to 2017); (b) the archive of the Finnish Environmental Institute <a href="https://www.syke.fi/">https://www.syke.fi</a> (for the period 2018–2020) and these series can be obtained after its representatives’ permission from the author. The daily series of water discharges at the sites located in the Russian Federation were extracted from (a) the yearly hydrological books published by the State Hydrological Institute <a href="http://www.hydrology.ru/en">http://www.hydrology.ru/en</a> (for the period from the beginning of observation to 2007); (b) the automated information system for state monitoring of water bodies <a href="https://gmvo.skniivh.ru/">https://gmvo.skniivh.ru/</a> (for the period 2008–2020) and these series are available from its web-site after a registration. </p> <p>The dataset consists of the CSV/TXT files, each file contains the long term series of the characteristics listed in the header: "year", "DFB" (date when a spring flooding period begins, day of year, DOY),"DFE" (date when the spring flooding period ends, DOY),"Length" (length of the spring flooding period, days), "DFMax" (date when the yearly maximum water discharge is recorded, DOY), "Qmax" (the yearly maximum water discharge, cubic m per second), "FRD" (the volume of spring flood expressed in mm per flooding period), "YRD" (volume of annual flow, expressed in mm per year),"Ftype" (the source of annual flood equaling to 1 of the yearly maximum water discharge is recorded in the spring flooding period or 0 if it is not). </p> <p>The dataset was obtained in the study funded by the Academy of Finland under the contract number 317999. It will become freely available once the manuscript is published. </p> <p>References</p> <p>Gudmundsson, L., Do, H. X., Leonard, M., & Westra, S. (2018), The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment, Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018.</p> <p>Shevnina E. (2013), Method to calculate characteristics of spring flood from daily water discharges, Problems of the Arctic and Antarctic, 1(95), pp. 12-21. In Russian</p>
Gridded reconstruction of monthly runoff for Northwest Russia
<p>Developed reconstructions of monthly runoff for Northwest Russia -- BASE and SOTA -- are the part of the manuscript "The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff" by G. Ayzel, L. Kurochkina, and S. Zhuravlev which was submitted in the Special Issue on “Hydrological Data: Opportunities and Barriers” of the Hydrological Sciences Journal (http://explore.tandfonline.com/cfp/est/hydrological-science-data).</p>
Demographic, economic, geospatial data for municipalities of the Central Federal District in Russia (excluding the city of Moscow and the Moscow oblast) in 2010-2016
<p>The database contains demographic, economic, geospatial data for 452 municipalities of the 16 administrative units of the Central Federal District in Russia (excluding the city of Moscow and the Moscow oblast) for 2010-2016.</p> <p>The sources of data are the municipal-level statistics of Rosstat, Google Maps data and calculated indicators. The statistical data were arranged by the year, the data on municipalities for which there were administrative and territorial transformations for the period under study were excluded (in some cases, the data were provided in accordance with the administrative-territorial demarcation as of 2016).</p> <p>Municipalities' websites were used to fill the lack of population information in individual municipalities for some years.</p> <p>Calculated variables were made to estimate a number of indicators per capita, to introduce additional demographic indicators (e.g. migration inflow rate), to bring price economic indicators to base year prices (2010). For example, indicators of income of the local budget, volumes of investments in fixed assets (excluding budgetary funds), level of wages are modified to a comparable form (to 2010 prices).</p> <p>The distances on roads in different units of measurement from the geographical center of municipalities to the center of the capital of the region are calculated using the Google Maps database.</p> <p>Data mapping was performed using ArcGIS software.</p> <p>The data set consists of</p> <p>1) Municipalities_CFD_Russia_2010_2016_ENG.xlsx - The database of demographic, economic, geospatial data for 452 municipalities of the 16 administrative units of the Central Federal District in Russia (excluding the city of Moscow and the Moscow oblast) for 2010-2016,</p> <p>2) MUNICIPALITIES_CFD_RUSSIA_SHAPE.rar - The shape-files for maps construction,</p> <p>3) Fig.1. Municipalities ENG.jpg - The map of studied administrative units and municipalities of the Central Federal District in Russia .</p>
Fig. 9 in A new genus of mongoliulid millipedes from the Far East of Russia, with a list of species in the family (Diplopoda, Julida, Mongoliulidae)
Fig. 9. Koiulus interruptus gen. et sp. nov., paratype, ♀, from upper course of river Ko, right vulva. A. Lateral view. B. Anterior view. C. Mesal view. D. Tip, posterior view; arrow points to unknown structure. E. Unknown structure from opercular seta. Abbreviations: BU = bursa; OP = operculum. Scale bars: A–C = 0.1 mm; D = 0.01 mm; E = 0.001 mm.
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.