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CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

Patterns of movement of marine species can reflect strategies of reproduction and dispersal, species’ interactions, trophodynamics, and susceptibility to change, and thus critically inform how we manage populations and ecosystems. On coral reefs, the density and diversity of metazoan taxa is greatest in dead coral and rubble, which is suggested to fuel food webs from the bottom-up. Yet, biomass and secondary productivity in rubble is predominantly available in some of the smallest individuals, limiting how accessible this energy is to higher trophic levels. We address the bioavailability of motile coral reef cryptofauna based on small-scale patterns of emigration in rubble. We deployed modified RUbble Biodiversity Samplers (RUBS) and emergence traps in a shallow rubble patch at Heron Island, Great Barrier Reef, to detect community-level differences in the directional influx of motile cryptofauna under five habitat accessibility regimes. The mean density (0.13–4.5 ind.cm-3) and biomass (0.14–5.2 mg.cm-3) of cryptofauna were high and varied depending on microhabitat accessibility. Emergent zooplankton represented a distinct community (dominated by the Appendicularia and Calanoida) with the lowest density and biomass, indicating constraints on nocturnal resource availability. Mean cryptofauna density and biomass were greatest when interstitial access within rubble was blocked, driven by the rapid proliferation of small harpacticoid copepods from the rubble surface, leading to trophic simplification. Individuals with high biomass (e.g., decapods, gobies, and echinoderms) were greatest when interstitial access within rubble was unrestricted. Treatments with a closed rubble surface did not differ from those completely open, suggesting that top-down predation does not diminish rubble-derived resources. Our results show that conspecific cues and species’ interactions (e.g., competition and predation) within rubble are most critical in shaping ecological outcomes within the cryptobiome. These findings have implications for prey accessibility through trophic and community size structuring in rubble, which may become increasingly relevant as benthic reef complexity shifts in the Anthropocene. We address the bioavailability of coral reef cryptofauna in rubble based on small-scale patterns of emigration. We adapted the accessibility of Rubble Biodiversity Samplers (RUBS), models used to standardise biodiversity sampling in rubble (Wolfe and Mumby 2020), to explore the local movement patterns of rubble-dwelling fauna, with inference to predation processes within and beyond the cryptobenthos. Five treatments were developed to detect community-level differences in the directional influx of motile cryptofauna under various habitat accessibility regimes. Four of these treatments were developed by modifying accessibility into RUBS (https://www.thingiverse.com/thing:4176644/files) to understand limitations on the directional influx and movement of cryptofauna within coral rubble patches using four treatments; (1) open (completely accessible), (2) interstitial access (top closed), (3) surficial access (sides and bottom closed), and (4) raised (above rubble substratum). The fifth treatment involved a series of emergence plankton traps, designed to target demersal cryptofauna that vertically migrate from within the rubble benthos at night, given emergent zooplankton biomass and diversity are greatest at night. Fieldwork was conducted over several weeks (11th September to 5th October 2021) in a shallow (~3–5 m depth) reef slope site on the southern margin of Heron Island (-23˚26.845’ S, 151˚54.732’ E), Great Barrier Reef, Australia (Fig. 1). All collections were conducted under the Great Barrier Reef Marine Park Authority permit G20/44613.1.

Poleward range extensions by warm-adapted sea urchins are switching temperate marine ecosystems from kelp-dominated to barren-dominated systems that favour the establishment of range-extending tropical fishes. Yet, such tropicalization may be buffered by ocean acidification, which reduces urchin grazing performance and the urchin barrens that tropical range-extending fishes prefer. Using ecosystems experiencing natural warming and acidification, we show that ocean acidification could buffer warming-facilitated tropicalization by reducing urchin populations (by 87%) and inhibiting the formation of barrens. This buffering effect of CO2 enrichment was observed at natural CO2 vents that are associated with a shift from a barren-dominated to a turf-dominated state, which we found is less favourable to tropical fishes. Together, these observations suggest that ocean acidification may buffer the tropicalization effect of ocean warming against urchin barren formation via multiple processes (fewer urchins and barrens) and consequently slow the increasing rate of tropicalization of temperate fish communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-07-26.

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.

This data was collected as a part of a mesocosm study to investigate the ecosystem impacts of ocean alkalinity enhancement, within the EU H2020 OceanNETs project. Nine mesocosms were deployed in Taliarte Harbour (Gran Canaria, Spain) and were regularly sampled using integrated water samplers between 10th September-25th October 2021. A gradient design was used in this experiment with a total of nine different alkalinity concentrations. Seawater alkalinity ranged between ambient (0 µeq kg-1 added alkalinity, OAE0) and 2400 µeq kg-1 additional alkalinity (OAE2400). The alkalinity levels increased in equal intervals of 300 µeq kg-1 across nine mesocosms (OAE0, OAE300, OAE600, OAE900, OAE1200, OAE1500, OAE1800, OAE2100, OAE2400). This data set contains metazoan zooplankton biomass (µgC per L) from these nine mesocosms. Biomass was calculated based on zooplankton abundances transformed using carbon mass conversion factors. Metazoan zooplankton were sampled with apstein net (ø17cm, mesh size 55µm, 64.06285L) hauls taken every two days (except for days 5 and 9). Zooplankton were size fractioned and assessed in the correspondent size class (small: 55-200µm; medium: 200-500µm; large: 500µm-3mm). Within each size class, all organisms were counted and identified to the lowest possible taxonomic level, and developmental stages were differentiated where possible. Zooplankton abundances (individuals per L) converted to carbon biomass (µgC per L) using biomass conversion factors. Conversion factors are obtained from different sources (Sanchez et al. (in prep)). Briefly: i) metazoan zooplankton functional groups were sampled and measured for carbon biomass using an elemental analyser at specific points throughout the experiment, ii) individual zooplankton were photographed, measured, and their biovolumes and carbon masses derived using standard conversions cited in the literature, iii) zooplankton conversion factors from KOSMOS Gran Canaria 2019 (https://doi.pangaea.de/10.1594/PANGAEA.971765). The experiment, which lasted 33 days, was divided into four response phases (see Sánchez et al. (in prep)): i) pretreatment (days 1 to 4, treatment was implemented on day 4), ii) immediate (days 5-10), iii) shorter term (days 11-22), iv) longer term (days 23 to 33). This data set is associated to the submission by Paul et al. (in review) (https://doi.pangaea.de/10.1594/PANGAEA.966941), so we refer to this data set for basic parameters like water temperature, salinity, pH and carbonate chemistry, to avoid repetition.