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Vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021.Ground vegetation was surveyed for different vegetation types within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were chosen for the survey. The assignment of a vegetation type is always unique to a site. Their cover on the circular forest plot was recorded in percent.In total, 84 vegetation types at 58 forest plots were assessed. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia.

Humanity’s role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the ‘anthropocene’, as humans are ‘overwhelming the great forces of nature’. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed ‘manufactured capital’, ‘technomass’, ‘human-made mass’, ‘in-use stocks’ or ‘socioeconomic material stocks’, they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with ‘real’ (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called ‘built structures’) represent the overwhelming majority of all socioeconomic material stocks. This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Spatial extent This subdataset covers the West Coast CONUS, i.e. CA OR WA For the remaining CONUS, see the related identifiers. Temporal extent The map is representative for ca. 2018. Data format The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided. Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types). Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e. t at 10m x 10m kt at 100m x 100m Mt at 1km x 1km Gt at 10km x 10km For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming. Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv. Material layers Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers): A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337. Further information For further information, please see the publication. A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gomez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, H. Haberl. Weighing the US Economy: Map of Built Structures Unveils Patterns in Human-Dominated Landscapes. In prep Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404. Acknowledgments We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

Lachgas (N2O) ist ein klimarelevantes Spurengas, welches auch zur Ozonzerstörung in der Stratosphäre beiträgt. Es herrscht Konsens darüber, dass eine Reduktion der N2O Emissionen anzustreben ist. Hauptquelle der N2O Freisetzung in Deutschland sind landwirtschaftlich genutzte Böden. Aufgrund des hohen N-Inputs über die Düngung wird die N2O-Emission stimuliert, da der Stickstoff als Substrat für die wesentlichen Prozesse der N2O-Bildung in Böden wie die Nitrifikation und Denitrifikation dient. Neben den hohen N2O-Emissionen während der Vegetationsperiode kann auch im Winter eine hohe N2O-Freisetzung in Zusammenhang mit Frost-Tau Zyklen auftreten. Der Anteil dieser Winteremissionen an der Jahresemission beträgt in Deutschland etwa 50%. Deshalb sind annuelle Datensätze eine unerlässliche Voraussetzung für die zuverlässige Bewertung von N2O-Reduktionsstrategien in Gegenden mit Winterfrost. Für landwirtschaftlich genutzte Böden liegt bereits eine Vielzahl an Untersuchungen zur Minderung der N2O-Freisetzung vor. Jedoch wurde die N2O-Freisetzung aus gemüsebaulich genutzten Böden nur selten untersucht. Keine der bisher durchgeführten Spurengasmessungen im intensiven Gemüsebau ist repräsentativ für die klimatischen Bedingungen Süddeutschlands. Durch den hohen N-Düngerinput (der zu hohen Gehalten an mineralischem Stickstoff im Boden führt) und stickstoffreiche Ernterückstände im Spätherbst sind hohe N2O-Jahresemissionen aus diesen Flächen zu erwarten. Im Rahmen dieser Studie wurden die N2O-Flussraten zwei Jahre lang in mindestens wöchentlicher Auflösung auf einer Gemüsebaufläche in Süddeutschland mit der geschlossenen Kammermethode ermittelt. Während der beiden Versuchsjahre wurde jeweils ein Satz Kopfsalat und darauffolgend ein Satz Blumenkohl angebaut. Um Aufschluss über die N2O-Quellen (Dünger, Ernterückstände, bodeninterne Mineralisation) zu erhalten wurde zusätzlich eine Studie mit 15N markiertem Ammonsulfatsalpeter (ASS) und Austausch markierter und unmarkierter Erntereste durchgeführt. Ferner wurden verschiedene Strategien zur Reduktion der N2O-Emissionen wie Düngerreduktion, Zusatz eines Nitrifikationshemmstoffes (3,4-Dimethylpyrazolphosphat, DMPP) und eine Depotdüngung hinsichtlich ihres Potentials zur Reduktion der N2O-Emissionen auf Jahresbasis getestet. Die Reduktion der N2O Emissionen sollte bei diesen Strategien wie folgt erreicht werden: Bei einer Reduktion des Dünger N-Inputs wurde eine Absenkung der Menge an mineralischem N im Boden erwartet und dadurch niedrigere Substratkonzentrationen für N2O produzierende Mikroorganismen. DMPP ist ein chemischer Hemmstoff, der die Nitrifikation auf enzymatischer Ebene inhibiert. Bei der Depotdüngung wird ammoniumreicher Dünger hoch konzentriert in Form eines Bandes im Boden abgelegt. Die hohen Ammoniumkonzentrationen sollen durch Ihre Toxizität die Nitrifikanten ebenfalls hemmen. Aufgrund der gehemmten Nitrifikation sollte einerseits die N2O-Bildung während der Nitrifikation direkt vermindert und andererseits die Denitrifikation über das geringere Nitratangebot limitiert werden. Es wurde eine sehr hohe zeitliche Variabilität der N2O-Flussraten beobachtet. Ausgeprägte Emissionsmaxima traten vor allem nach N-Düngungsmaßnahmen, nach der Einarbeitung von Ernterückständen (besonders in Kombination mit der N-Düngung), nach Wiederbefeuchtung von trockenem Boden im Hochsommer sowie nach dem Auftauen von gefrorenem Boden im Winterhalbjahr auf. Die kumulativen Jahresemissionen in der konventionell (breitflächig) gedüngten Variante beliefen sich im ersten und zweiten Versuchsjahr auf 8.8 und 4.7 kg N2O-N ha-1 a-1. Die N-Düngung erfolgte hier nach dem kulturbegleitenden Nmin Sollwertsystem. Die N2O-Emissionsfaktoren lagen mit 1.6% und 0.8% innerhalb des Unsicherheitsbereiches von 0.3 - 3%, den der Weltklimarat (IPCC; 2006) in seinen Richtlinien zur Berechnung Nationaler Treibhausgasinventare angibt. Es konnte ein positiver Zusammenhang zwischen den mittleren Nitratgehalten des Oberbodens und den kumulativen N2O-Emissionen in den beiden Versuchsjahren (r2=0.44 und 0.68) sowie zwischen den N-Überschüssen und den kumulativen N2O Emissionen der Düngersteigerungsreihe (r2=0.95) im ersten Versuchsjahr nachgewiesen werden. Eine Reduktion der N-Düngermenge von praxisüblicher Düngung auf Düngung nach dem kulturbegleitenden Nmin Sollwertsystem führte im ersten Versuchsjahr zu einer Minderung der N2O-Jahresemissionen um 17%, die Gemüseerträge wurden durch die verminderte N-Gabe nicht beeinträchtigt. Im zweiten Versuchsjahr wurde die mittlere N2O-Emission bei reduzierter N-Gabe um 10% gesenkt, dieser Effekt war jedoch statistisch nicht abgesichert. Eine weitere Absenkung der Düngermenge um 20% führte zwar zu einer weiteren Minderung der N2O-Emission, allerdings waren im ersten Versuchsjahr dadurch auch die Kopfsalaterträge geringer. Eine weitere Absenkung der Düngermenge ist somit nicht empfehlenswert. Für die DMPP-Anwendung liegen durch diese Arbeit erstmals Jahresdaten zur N2O-Freisetzung vor. Die Anwendung von DMPP verringerte die N2O-Emissionen in den beiden Versuchsjahren signifikant um mehr als 40%. Dieser Effekt trat sowohl während der Vegetationsperiode als auch im Winter auf. Der Grund für die Emissionsminderung im Winter konnte nicht geklärt werden: Der Abbau des Wirkstoffs DMPP ist temperaturabhängig und wird unter den gegebenen Temperaturen im Sommer mit ca. 6 bis 8 Wochen veranschlagt. Die von uns beobachteten Minderungseffekte traten jedoch auch im Winter auf, also noch 3 Monate nach Applikation des Wirkstoffes. Ferner wurde eine ebenfalls verminderte CO2-Freisetzung gemessen, die ein Hinweis auf einen Effekt des DMPP auf heterotrophe Mikroorganismen oder zumindest deren C-Umsatz sein könnte. Aufgrund des hohen N2O-Minderungspotentials scheinen weiterführende Untersuchungen zu funktionellen und strukturellen Veränderungen der mikrobiellen Biomasse nach DMPP-Anwendung sinnvoll. Eine Depotdüngung mit ASS führte nicht zur erhofften Reduktion der N2O Freisetzung auf Jahresbasis. Selbst der Ersatz von ASS durch (nitratfreies) Ammoniumsulfat führte nicht zu einer Reduktion der Emissionen. Vermutlich gehen die relativ hohen Flussraten auf die mikrobiell intakten Bereiche um die Düngerdepots zurück, in denen die Nitrifikation abläuft und in denen durch die hohen Nitratgehalte ideale Bedingungen für denitrifizierende Mikroorganismen herrschten. Nach einem Jahr fand sich ein Großteil des mit dem Dünger ausgebrachten 15N im Boden wieder. Nur 13 - 15% wurden über die marktfähige Ware aufgenommen. 1.4% des 15N gingen in Form von N2O-N verloren. Die Wiederfindungsrate nach einem Jahr betrug 70%. Die Verluste an 15N sind vermutlich auf Nitratauswaschung oder gasförmige Verluste in Form von N2 oder NOx zurückzuführen. Verglichen mit dem Getreideanbau ist die N-Ausnutzung im Gemüsebau also selbst bei optimierter Düngung wesentlich niedriger. Die Messung der 15N Häufigkeit im N2O zeigte, dass der Hauptteil der N2O-Emissionen (38%) aus den Ernteresten des Blumenkohls stammte (genauergesagt Dünger-N, der über die Pflanzen in die Ernteresten eingelagert wurde). 26% und 20% stammten jeweils direkt aus dem Dünger zu Kopfsalat und Blumenkohl. Bodeninterne Quellen waren für 15% der Gesamtemission verantwortlich, während der Beitrag der Erntereste des Kopfsalats aufgrund der geringen C- und N-Mengen vernachlässigbar gering war. Der beträchtliche Anteil der N2O-Emissionen aus den Ernteresten des Blumenkohls wurde darauf zurückgeführt, dass das System zeitweise C-limitiert war und so durch das organische Material Elektronendonatoren zur Verfügung gestellt wurden. Zudem wird beim Abbau von organischer Substanz in Böden O2 verbraucht, was bei hohen Wassergehalten zur Bildung anaerober Kompartimente und so zu idealen Bedingungen für Denitrifikanten führt. Besonders der kombinierte Eintrag von organischer Substanz und mineralischem N-Dünger erhöhte die N2O-Emissionen. Daher wurde in einem Zusatzversuch zu Mangold getestet, inwiefern eine Desynchronisation der Einarbeitung von Ernteresten und der mineralischen N-Düngung durch Wartezeiten (bis zu 3 Wochen) zu einer Emissionsminderung beiträgt. Je länger die Einarbeitung der Erntereste von der N-Düngerapplikation entfernt lag, desto geringer waren auch die N2O-Emissionen, allerdings war dieser Effekt auf Jahresbasis nicht statistisch gesichert. In einem Inkubationsversuch mit Mikrokosmen wurde der Effekt von verschiedenen C/N-Verhältnissen von Blumenkohlernteresten sowie die Einarbeitung reduzierter und erhöhter Mengen modellhaft untersucht. Es zeigte sich, dass aufgrund des generell hohen Nitratangebots in den Kosmen lediglich die verschiedenen Ernterestmengen einen Effekt auf die N2O-Freisetzung zeigten. Die N2O-Emission stieg mit der Menge an Ernteresten an. Insgesamt konnte in dieser Arbeit gezeigt werden, dass im Gemüsebau relativ hohe absolute N2O-Emissionen erwartet werden können, auch wenn der relative Anteil (Emissionsfaktoren) im Rahmen des IPCC-Unsicherheitsbereichs lag. Weitere Untersuchungen sind nötig, um die genauen Wirkungsmechanismen von DMPP auf die Bildung von N2O im Feld zu verstehen. Die vorliegende Studie belegt, dass der Vermeidung von N-Überschüssen und der Entwicklung von Strategien zum Ernterestmanagement im Gemüsebau große Bedeutung zur Reduktion der N2O-Emissionen zukommt. Nitrous oxide (N2O) is a potent greenhouse gas which is also involved in stratospheric ozone depletion. There is consensus that a reduction in N2O emissions is ecologically worthwhile. Agricultural soils are the major source of N2O emissions in Germany. It is known that high N-fertilization stimulates N2O emissions by providing substrate for the microbial production of N2O by nitrification and denitrification in soils. However, outside the vegetation period, winter freeze/thaw events can also lead to high N2O emissions. Winter emissions constitute about 50% of total emissions in Germany. Therefore, annual datasets are a prerequisite for the development of N2O mitigation strategies in regions with winter frost. Many studies have investigated mitigation strategies for N2O emissions from agricultural soils. However, N2O release from vegetable production has seldom been studied. None of the existing trace gas measurements on intensive vegetable production is representative for the climatic conditions of Southern Germany. Due to the high fertilizer N-input (resulting in high levels of mineral N in the soil) and N-rich residues in late autumn, high annual N2O emissions are to be expected. N2O fluxes were measured from a soilcropped with lettuce and cauliflower in Southern Germany by means of the closed chamber method, at least weekly, for two years. An additional study was conducted using 15 N labeled ammonium sulfate nitrate (ASN) fertilizer and exchange of labeled and unlabeled residues to obtain information about the sources (fertilizer, residues, soil internal mineralization) of N2O emissions. Different mitigation strategies such as fertilizer reduction, addition of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) and banded fertilization were evaluated with respect to their reduction potential on an annual base. Fertilizer reduction is supposed to decrease the soil mineral N level, reducing the available substrate for N2O producing microorganisms. DMPP is a chemical compound which inhibits nitrification enzymatically. In banded fertilization, ammonium rich fertilizer is applied in a depot. This high concentration is also supposed to inhibit nitrification as it is toxic to microorganisms. N2O emissions should be firstly reduced directly by this inhibition of nitrification and secondly, by a lower nitrate content in soil resulting in less N2O release due to denitrification. A high temporal variability in N2O fluxes was observed with emission peaks after N-fertilization, after the incorporation of crop residues (especially in combination with N-fertilization), after rewetting of dry soil and after thawing of frozen soil in winter. Total cumulative annual emissions were 8.8 and 4.7 kg N2O-N ha-1 a-1 for the first and second experimental year in the conventionally (broadcast) fertilized treatment. This treatment was fertilized according to the German Target Value System. N2O emission factors were 1.6 and 0.8%. This is within the range of 0.3 - 3% which is cited in the Guidelines for the Calculation of National Greenhouse Gas Inventories proposed by the Intergovernmental Panel of Climate Change (IPCC). A positive correlation was found in both years between the mean nitrate content of the top soil and the cumulative N2O emissions of all treatments (r2=0.44 and 0.68) as well as between the N-surpluses and the cumulative N2O emissions of the different fertilizer levels during the first year (r2=0.95). Fertilizer reduction from fertilization according to good agricultural practice following the recommendations of the German Target Value System reduced annual N2O emissions by 17% in the first experimental year without yield reduction. For the second year, the reducing effect was 10%, but statistically not significant. Another fertilizer reduction of a further 20% reduced N2O emissions, but also resulted in lower lettuce yields in the first year. Therefore, an additional fertilizer reduction is not recommendable. This work provides, for the first time, annual datasets on the effect of DMPP-application on N2O emissions. Addition of DMPP significantly reduced annual N2O emissions by > 40% during both years, there was also a pronounced effect, both during the vegetation period and winter. The reason for the reducing effect in winter is not yet clear because the degradation of the active agent DMPP is temperature dependent and should take about 6 to 8 weeks under summer climatic conditions. However, we still observed significant reductions in N2O emissions in winter, about 3 months after the application. Furthermore, a reduction in CO2 release was observed indicating a possible influence on heterotrophic activities or at least on their C-turnover. Due to its high N2O mitigation potential, further investigations concerning the functional and structural changes in microbial biomass after DMPP application are needed. Banded fertilization with ASN did not result in the expected reduction in N2O emissions on an annual base. Even when exchanging the ASN fertilizer by nitrate-free ammonium sulfate, N2O emissions were not diminished. We assume that the high emissions were derived from the microbially intact surroundings of the depots, where nitrification was not inhibited and nitrate concentrations were probably very high, creating ideal conditions for denitrification. After one year, the major part of the fertilizer-15N was found in the soil. Only between 13 -15% of the fertilizer was taken up by the marketable plant parts. 1.4% of the 15N was lost as N2O-N. Total 15N recovery was 70% after one year. The losses of non-recovered N were probably caused by nitrate leaching or as gaseous compounds such as N2 or NOx. Compared to cereal production systems, the N use efficiency of this vegetable production system is much lower, even with an optimized fertilization strategy. The measurement of 15N abundances in the N2O revealed that the most significant part of the emissions (38%) was derived from the fertilizer-N which had been taken up by cauliflower residues. N2O emissions directly derived from lettuce and cauliflower fertilizer contributed 26% and 20% respectively while N2O emissions from soil internal N pools accounted for 15%. The contribution of lettuce residues was negligible due to their low amount of C and N. The reason for the high importance of the cauliflower residues was ascribed to the temporarily C-limitation of the system and the provision of electron donators by organic material. Furthermore, O2 is consumed during their degradation leading to the formation of anaerobic microsites when soil moisture is high. These sites offer ideal conditions for denitrification. Especially the combination of mineral N-fertilization and input of organic substance was found to increase N2O emissions. Therefore, the influence of a de-synchronization of the incorporation of crop residues and the mineral N-fertilization by waiting periods of up to 3 weeks was tested in an additional field trial during the cultivation of chard. The longer the waiting time between incorporation of crop residues and N-fertilizer application was, the lower were the N2O emissions. However, the effect was not statistically significant on an annual base. In an additional microcosm incubation model study, the effect of reduced and increased input as well as of different C/N-ratios of cauliflower residues was analyzed. It was shown that due to the high nitrate level in the microcosms only the amount of residue input has an effect on the N2O emissions. The N2O emissions increased with increased amount of cauliflower residues. Although the emission factors were within the range given by the IPCC, the absolute annual N2O emission was high in intensive vegetable production due to the high N-input. Further research is required in order to fully understand the effect of DMPP on the processes of N2O production in the field. Our study underlines the importance of avoiding N-surpluses and of strategies for residue management to reduce N2O emissions in intensive vegetable production.

Detailed measurements on soil, plant and atmosphere are required for the development and validation of crop growth and agroecosystem models. These measurements should be available with a high temporal resolution. With the aim of creating a growth model for winter wheat, an experiment with winter wheat under integrated cultivation conditions was carried out at the intensive experimental field of the Müncheberg Research Centre for Soil Fertility, Germany, between 1979 and 1981, both with and without irrigation. Field chambers were used for daily measurements of the CO2 balance of the crop stand. The daily evaporation was measured with two different evaporation pans. The different biomass components of the winter wheat crop stand were measured in weekly intervals from April to harvest in July/August. The different biomass components were analysed in the laboratory concerning their carbon, nitrogen, phosphorus and potassium content. Based on this coherent data set, the growth model TRITSIM for winter wheat was developed at the Müncheberg Research Centre for Soil Fertility in the 1980s. TRITSIM was incorporated into the complex agroecosystem model AGROSIM-WHEAT of the Research Institute of Plant Protection Eberswalde, Germany, for the identification of optimal plant protection measures under practical field conditions. The data set presented here can also be the basis for the verification and validation of further winter wheat growth and/or agroecosystem models.

These data were collected as part of a case study for the ipaast project. The aim of the survey was to produce datasets interoperable for applications in archaeology and precision agriculture. The OptRx® Crop Sensors (AgLeader Technology, Ames, IO, USA) measure the reflectance in the 630–685 nm (red), 695–750 nm (RE red edge) and 760–850 nm (NIR—Near InfraRed) wavebands. Using those wavebands, NDVI and NDRE indexes are calculated. NDVI and NDRE are vegetative indexes obtained from the red, red-edge and NIR wavebands with formulas 1 and 2: NDVI = NIR−REDNIR+RED ; NDRE= NIR−RENIR+RE The two index values range from -1 (bare ground or water) to 1 (highly vigorous vegetation). To collect data, the sensor was mounted on a ground vehicle, a Kubota B2420 tractor. The sensor was paired with a GNNS receiver, GPS 6500 from AgLeader Technology (Ames, IO, USA). The instrumentation was coupled with the hardware and the rough book (Panasonic ToughPad FG-Z1, Panasonic Core. It was possible to install the sensor facing the ground using a metal bracket positioned on the front of the tractor. The sensor was positioned 1.15 m from the ground, emitting a rectangular footprint of 1.14 m in length and 20cm in width. The data were collected every 30 cm in alternate rows. 12 rows in total were analysed, covering a surface of 1.07 ha. Data were processed on QGIS. First, the data was interpolated with the Inverse Distance Weighting (IDW) function. The function was set up with a distance coefficient P of 4, with 40 rows and 98 columns. A Gaussian filter with a standard deviation value of 2 and a range of research of 3 was subsequently applied to create a representative raster.

Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks. This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Spatial extentThis subdataset covers the South CONUS, i.e. AL AR FL GA KY LA MS NC SC TN VA WV For the remaining CONUS, see the related identifiers. Temporal extentThe map is representative for ca. 2018. Data formatThe data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided. Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types). Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e. t at 10m x 10m kt at 100m x 100m Mt at 1km x 1km Gt at 10km x 10km For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming. Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv. Material layersNote that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers): A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337. Further informationFor further information, please see the publication.A web-visualization of this dataset is available here.Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. PublicationD. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. Nature Communications 14, 8014. https://doi.org/10.1038/s41467-023-43755-5 FundingThis research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404. AcknowledgmentsWe thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

A sublittoral transect (P3) in the North of Helgoland that had been investigated ~40 years earlier by Lüning (1970) was traversed again. Scuba dives were carried out between 24.06.2005 and 19.08.2005. For each sampling point, time, date and coordinates were given as well as the corrected depth in m mean low water spring tide. Along the transect, substrate and topography were recorded. Relative frequency and cover of 32 species grown attached to the seafloor and cover of 12 epiphytic species were obtained.

Datasets associated with Agostini, S., Houlbreque, F., Biscéré, T., Harvey, B. P., Heitzman, J. M., Takimoto, R., et al. (2020). Greater mitochondrial energy production provides resistance to ocean acidification in ‘winning’ hermatypic corals. Front. Mar. Sci. 7. doi:10.3389/fmars.2020.600836.