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This file contains two supplemental videos to chapter 4 of the PhD thesis of Evert de Froe which is registered as follows: ISBN/EAN: 978-90-6266-643-0 Title: Dinner's Served in the Deep Sea Subtitle: Environmental conditions, organic matter transport, and benthic fluxes at cold-water coral and sponge communities in the deep sea. Author: Froe, Evert de Uitgever: Universiteit Utrecht,Bibliotheek Geowetenschappen/TNO Bibliografische imprint: Universiteit Utrecht,Bibliotheek Geowetenschappen/TNO NUR-code: 930 NUR-omschrijving: Aardwetenschappen algemeen Reeks: Utrecht Studies in Earth Sciences Reeksnummer: 273 Druk: 1 Illustraties: Ja Aantal pagina's: 211 Taal: Engels Verschijningsvorm: Paperback / softback Verschijningsdatum: 13-03-2023

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-2 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). 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”. {"references": ["Stefan Kruse, Mareike Wieczorek, Florian Jeltsch and Ulrike Herzschuh (2016) Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix. Ecological Modelling, 338, 101\u2013121. http://dx.doi.org/10.1016/j.ecolmodel.2016.08.003 Additional data and results are available at https://doi.pangaea.de/10.1594/PANGAEA.863584", "Stefan Kruse (2023). StefanKruse/LAVESI: LAVESI-WIND with landscape (v2.0). Zenodo. https://doi.org/10.5281/zenodo.7505539", "Shevtsova, Iuliia, Herzschuh, Ulrike, Heim, Birgit, & Kruse, Stefan. (2023). Simulated above ground biomass of forests (larch) aggregated over the vicinity of the Ilirney lake system region, Chukotka, Russia [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7505616", "Shevtsova I, Herzschuh U, Heim B, Schulte L, St\u00fcnzi S, Pestryakova LA, Zakharov ES, Kruse S: Recent above-ground biomass changes in central Chukotka (Russian Far East) using field sampling and Landsat satellite data. Biogeosciences, 18, 3343\u20133366, https://doi.org/10.5194/bg-18-3343-2021, 2021."]} This work has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme "Kohlenstoff im Permafrost KoPf" (grant no. 03F0764A), by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852).

Forest density estimates visually determined by describing the amount of present trees satellite imagery from Esri basemap (Esri) at an area of ~30x30 m qualitatively for 6515 stratified sampled locations at an equal number of locations based on elevation, aspect and slope angle. The density was categorized ranging from 1: single trees to 4: dense tree stands present, and contains a 0: no trees present. Format: ESRI shapefile, points; projection UTM58N; extent: 642085.1, 654775.1, 7462263, 7492833 m (xmin, xmax, ymin, ymax) This work has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme "Kohlenstoff im Permafrost KoPf" (grant no. 03F0764A), by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852). {"references": ["Esri: \"High-resolution satellite and aerial imagery, typically within 3-5 years\" [basemap]. Scale Not Given. \"World Imagery\". https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9, Accession: 15 December 2020."]}

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-2) 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. Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 640008.2, 649998.2, 7475006, 7494716 m (xmin, xmax, ymin, ymax) {"references": ["Stefan Kruse, Mareike Wieczorek, Florian Jeltsch and Ulrike Herzschuh (2016) Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix. Ecological Modelling, 338, 101\u2013121. http://dx.doi.org/10.1016/j.ecolmodel.2016.08.003 Additional data and results are available at https://doi.pangaea.de/10.1594/PANGAEA.863584", "Stefan Kruse: StefanKruse/LAVESI: LAVESI-WIND with landscape (v2.0). Zenodo. https://doi.org/10.5281/zenodo.7505539, 2023."]} This work has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme "Kohlenstoff im Permafrost KoPf" (grant no. 03F0764A), by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852).

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-2) 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). This data set is related to the data set of Kruse (2023). Format: csv, with headers 1-year, Year in CE, 2-average, mean AGB, in kg m-2 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”. {"references": ["Stefan Kruse, Mareike Wieczorek, Florian Jeltsch and Ulrike Herzschuh (2016) Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix. Ecological Modelling, 338, 101\u2013121. http://dx.doi.org/10.1016/j.ecolmodel.2016.08.003 Additional data and results are available at https://doi.pangaea.de/10.1594/PANGAEA.863584", "Stefan Kruse (2023). StefanKruse/LAVESI: LAVESI-WIND with landscape (v2.0). Zenodo. https://doi.org/10.5281/zenodo.7505539", "Shevtsova, Iuliia, Herzschuh, Ulrike, Heim, Birgit, & Kruse, Stefan. (2023). Simulated above ground biomass of forests (larch) in the vicinity of the Ilirney lake system region, Chukotka, Russia [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7505549"]} This work has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme "Kohlenstoff im Permafrost KoPf" (grant no. 03F0764A), by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852).

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: Elevation: 0-400 m 400-450m 450-500m 500-600m 600-650m 650-700m 700-1000m 1000-1500m Slope: 0-2° 2-4° 4-6° 6-8° 8-10° 10-12° 12-16° 16-18° 18-20° 20-25° 25-50° Aspect: 0-45° 45-90° 90-135° 135-180° 180-225° 225-270° 270-315° 315-360° Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 642010.1, 654910.1, 7462218, 7492908 m (xmin, xmax, ymin, ymax) {"references": ["Krieger G, Zink M, Bachmann M, Br\u00e4utigam B, Schulze D, Martone M, Rizzoli P, Steinbrecher U, Antony JW, De Zan F, Hajnsek I, Papathanassiou K, Kugler F, Rodriguez Cassola M, Younis M, Baumgartner S, L\u00f3pez-Dekker P, Prats P, Moreira A: TanDEM-X: a radar interferometer with two formation-flying satellites. Acta Astronautica, 89, 83\u201398, https://doi.org/10.1016/j.actaastro.2013.03.008, 2013."]} This work has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme "Kohlenstoff im Permafrost KoPf" (grant no. 03F0764A), by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852).

Abstract The discovery of stimuli-responsive high affinity host–guest pairs with potential applications under biologically relevant conditions is a challenging goal. This work reports a high-affini...

Data and code for "Mohammed Taha, H., Aalizadeh, R., Alygizakis, N. et al. The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry. Environ Sci Eur 34, 104 (2022). https://doi.org/10.1186/s12302-022-00680-6"

The tropical Angolan upwelling system is a highly productive ecosystem with a distinct seasonal cycle in surface temperature and primary production. The lowest sea surface temperature, strongest cross-shore temperature gradient, and maximum productivity occur in austral winter when seasonally prevailing upwelling favorable winds are weakest. A multi cruise dataset of microstructure profiles collected between 2013 and 2022 in the tropical Angolan upwelling system was used to analyze the importance of mixing for cooling of the mixed layer. The data were collected during six cruises on board of the R/V Meteor. The results show that cooling due to turbulent heat fluxes at the base of the mixed layer is an important cooling term. This turbulent cooling, that is strongest in shallow shelf regions, is capable of explaining the observed negative cross-shore temperature gradient.