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This dataset contains spatial predictions of the potential environmental spaces for pingos, ice-wedge polygons and rock glaciers across the Northern Hemisphere permafrost areas. The potential environmental spaces, i.e. conditions where climate, topography and soil properties are suitable for landform presence, were predicted with statistical ensemble modelling employing geospatial data on environmental conditions at 30 arc-second resolution (~1 km). In addition to the baseline period (1950-2000), the predictions are provided for 2041-2060 and 2061-2080 using climate-forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). The resulting dataset consists of five spatial predictions for each landform in GeoTIFF format.The data provide new information on 1) the fine-scale spatial distribution of permafrost landforms in the Northern Hemisphere, 2) the potential future alterations in the environmental suitability for permafrost landforms due to climate change, and 3) the circumpolar distribution of various ground ice types, and can 4) facilitate efforts to inventory permafrost landforms in incompletely mapped areas.

The data contains vulnerability estimates (climate niche factor analysis) for 49 native fish species in the upper Danube River basin. The upper Danube River basin is mainly located in Germany and Austria. The time frame covered is 300 years from 1800 to 2100 including two Representative Concentration Pathways, RCP 4.5 and RCP 8.5. Vulnerability estimates are calculated for three time frames (1800-1830; 1900-1930and 2070-2100 (including two RCPs)) with the time frame 1970-2000 as the baseline. In all files the zone column gives the basin ID for the master basins layer. The mean column gives the mean vulnerability estimate for a sub-basin for a certain species. For the future scenarios the different predictions based on the different GCM-RCM combinations have to be combined using the median and the zone as unique identifier.

Zooplankton treatment: HZ: zooplankton added, LZ: Zooplankton removedCarbon treatment: 0C: No glucose addition, 0.5: 0.5 x Redfield. 1: 1xRedfield, 2: 2xRedfield, 3: 3XRedfieldpH Treatment:NpH: Normal pH, LpH: Low pH

The “Hydroblack91” dataset is based on samples collected in the summer of 1991 and covers part of North-Western in front of Romanian coast and Western Black Sea (Bulgarian coasts) (between 43°30' - 42°10' N latitude and 28°40'- 31°45' E longitude). Mesozooplankton sampling was undertaken at 20 stations. The whole dataset is composed of 72 samples with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length.Mesozooplankton abundance: The collected materia was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987.Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).

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.

Coastal and intertidal habitats are at the forefront of anthropogenic influence and environmental change. The species occupying these habitats are adapted to a world of extremes, which may render them robust to the changing climate or more vulnerable if they are at their physiological limits. We characterized the diurnal, seasonal and interannual patterns of flux in biogeochemistry across an intertidal gradient on a temperate sandstone platform in eastern Australia over 6 years (2009–2015) and present a synthesis of our current understanding of this habitat in context with global change. We used rock pools as natural mesocosms to determine biogeochemistry dynamics and patterns of eco‐stress experienced by resident biota. In situ measurements and discrete water samples were collected night and day during neap low tide events to capture diurnal biogeochemistry cycles. Calculation of pHT using total alkalinity (TA) and dissolved inorganic carbon (DIC) revealed that the mid‐intertidal habitat exhibited the greatest flux over the years (pHT 7.52–8.87), and over a single tidal cycle (1.11 pHT units), while the low‐intertidal (pHT 7.82–8.30) and subtidal (pHT 7.87–8.30) were less variable. Temperature flux was also greatest in the mid‐intertidal (8.0–34.5°C) and over a single tidal event (14°C range), as typical of temperate rocky shores. Mean TA and DIC increased at night and decreased during the day, with the most extreme conditions measured in the mid‐intertidal owing to prolonged emersion periods. Temporal sampling revealed that net ecosystem calcification and production were highest during the day and lowest at night, particularly in the mid‐intertidal. Characterization of biogeochemical fluctuations in a world of extremes demonstrates the variable conditions that intertidal biota routinely experience and highlight potential microhabitat‐specific vulnerabilities and climate change refugia. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) 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 2020-11-30.

Fresh biomass of invertebrates in sweep net samples of all 60 plots plus 4 sun-coffee-plantations. We used 100 sweeps with a 30-cm diameter sweep net along two parallel, permanently marked 50-m transects on the plots to sample invertebrate biomass per plot in the warm dry season and cold dry season. All invertebrates ≥ 1 mm were lumped to one sample per plot and season, which was immediately weighed to obtain fresh biomass. Fresh biomass of invertebrates in sweep net samples of all 60 plots plus 4 sun-coffee-plantations.Biomass of invertebrates = sweep net sample of 2x50 sweeps along the transects

Total mesozooplankton biomass was measured as dry weight on a fresh sample. Samples were sieved on 200 µm nitex, briefly rinsed with distilled water to remove salt, transferred on pre-weighted alluminium foil and placed in an oven at 60°C. The samples were weighted on a microbalance after 24 hours and again 2-3 times within the following seven days, until the weight was constant. This latter value was considered as dry weight.