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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.

This project contains the data obtained as a result of the Preludium Grant no 2022/45/N/ST8/01425 of the Polish National Science Centre fundings. Within the "Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control" project, two main research tasks were defined: 1. Post-processing and analysis of acoustic measurements using beamforming techniques to investigate RVGs effect on acoustic sources 2. Post-processing and analysis of Particle Image Velocimetry (PIV) data to investigate a flow structure downstream of RVG The resutls from these tasks are uploaded here. The details of the data are included in the EOP_medata_1.docx document uploaded. Further information regarding the data is published in the paper https://www.researchgate.net/publication/380825438_Aeroacoustic_effect_of_boundary_layer_separation_control_by_rod_vortex_generators_on_the_DU96-W-180_airfoil

This file contains the raw dataset used in the manuscript "Tailored Nanoscale Plasmon-Enhanced Vibrational Electron Spectroscopy" published in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659) Data has been acquired using Nion Swift (https://nionswift.readthedocs.io/en/stable/). Experimental details can be found in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659). The dataset has been analyzed using the following Python libraries: Numpy, Scipy, Hyperspy, Matplotlib EELS hyperspectral images have been aligned using the Hyperspy "align1D" method. Aligned EELS hyperspectral images are saved in files finished with "_Aligned.hspy": For the strong coupling experiments: Tip 1 is on hBN Tip 2 is on vacuum For each of the nanowires tips, a file with the fitted coefficients are available, as well as a plot of the data and the fitted curve. Datasets have been fitted with gaussian and/or lorentizan functions, as described in the published text. Any question can be forwarded to the corresponding authors of the published text. Other funding: 1) National Agency for Researchunder the program of future investment TEMPOS-CHROMATEM (reference no. ANR-10-EQPX-50); 2) Spanish MINECO (MAT2017-88492-R and SEV2015-0522); 3) the Catalan CERCA Program; 4) Fundació Privada Celle;

The aim of this study was to identify the attitudes of the public in the United States and in 12 European countries towards foreign policy issues and transatlantic issues. The survey concentrated on issues such as: United States and European Union (EU) leadership and relations, favorability towards certain countries, institutions and people, security, cooperation and the perception of threat including issues of concern with Afghanistan, Iran, and Russia, energy dependence, economic downturn, and global warming, Turkey and Turkish accession to the EU, promotion of democracy in other countries, and the importance of economic versus military power. Several questions asked of respondents pertained to voting and politics including whether they discussed political matters with friends and whether they attempted to persuade others close to them to share their views on politics which they held strong opinions about, vote intention, their assessment of the current United States President and upcoming presidential election, political party attachment, and left-right political self-placement. Demographic and other background information includes age, gender, race, ethnicity, religious affiliation and participation, age when stopped full-time education and stage at which full-time education completed, occupation, number of people aged 18 years and older living in the household, type of locality, region of residence, prior travel to the United States or Europe, and language of interview. computer-assisted personal interview (CAPI); computer-assisted telephone interview (CATI); paper and pencil interview (PAPI)The original data collection was carried out by TNS, Fait et Opinion -- Brussels on request of the German Marshall Fund of the United States.The codebook and setup files for this collection contain characters with diacritical marks used in many European languages.A split ballot was used for one or more questions in this survey. The variable SPLIT defines the separate groups.For data collection, the computer-assisted face-to-face interview was used in Poland, the paper and pencil interview was used in Bulgaria, Romania, Slovakia and Turkey, and the computer-assisted telephone interview was used in all other countries.Additional information on the Transatlantic Trends Survey is provided on the Transatlantic Trends Web site. (1) Multistage random sampling was implemented in the countries using face-to-face interviewing. Sampling points were selected according to region, and then random routes were conducted within these sampling points. Four callbacks were used for each address. The birthday rule was used to randomly select respondents within a household. (2) Random Digit Dialing was implemented in the countries using telephone interviewing. Eight callbacks were used for each telephone number. The birthday rule was used to randomly select respondents within a household. The adult population aged 18 years and over in 13 countries: Bulgaria, France, Germany, Italy, the Netherlands, Poland, Portugal, Romania, Slovakia, Spain, Turkey, the United Kingdom, and the United States. Smallest Geographic Unit: country Response Rates: The total response rate for all countries surveyed is 23 percent. Please refer to the "Technical Note" in the ICPSR codebook for additional information about response rate. Please refer to the "Technical Note" in the ICPSR codebook for further information about weighting. Datasets: DS1: Transatlantic Trends Survey, 2008

Material compiled for analysis in this paper: Ueckerdt F, Bauer C, Dirnaichner A, Everall J, Sacchi R, Luderer R (2021) Potential and risks of hydrogen-based e-fuels in climate change mitigation. Nature Climate Change. The material includes: 1) a spreadsheet file with technoeconomic data 2) an R Markdown script which is the source code for an interactive dashboard used to visualise (1) 3) a README file to assist with navigation of the data in (1) 1) The spreadsheet data contains CAPEX, efficiency and other supplementary data for small to large scale electrolysers for current, and future years. Data was collected based on a Literature Review of a variety of academic and industry sources conducted during the course of the title paper development. The data are differentiated by several categories including electrolysis method, source publication year and literature type. Care was taken to avoid recycled cost values, and to focus on the currency of the data, with values included to indicate the oldest reference year of any cited literature. 2) The R Markdown script in combination with the spreadsheet data is used as a basis for an interactive dashboard which can be run with an R installation and the supporting packages, or viewed online at https://h2.pik-potsdam.de/H2Dash/

Sampling — We studied 20 populations of Anthyllis vulneraria along a 2400 km latitudinal gradient from the center of its distribution in Central Europe (46.4 °N) to its northern distribution limit in Scandinavia (68.1 °N) and 20 populations along three elevational gradients in the French, Swiss and Austrian Alps from 500 m to the elevational limit at 2500 m a.s.l. (Fig. 1; Daco et al., 2021; Appendix S1, Table S1; see Supplemental Data with this article). The length of the two gradients was chosen to correspond to a change of 11.5 °C in annual mean temperature. In summer 2015, towards the end of the flowering period, we recorded at each site the elevation above sea level, latitude and longitude with a GPS (eTrex 20, Garmin Ltd.). We collected fruitheads from 20 plants/population along a 20 m transect and placed them in separate paper bags. To compare trait values in the field and in the common garden, for each mother plant we determined the height of the tallest flowering stem, the diameter of the rosette, the width of the terminal leaflet of the longest basal leaf, the number of stems with flowers (stems), and the number of flowerheads. In the laboratory, we extracted all healthy seeds (i.e. green and large) from the fruitheads of each mother plant. Cultivation in the common garden — In April 2016, ten seeds from each mother plant were scarified by rubbing them between sheets of sand paper, placed on moist filter paper in Petri dishes and kept at 20 °C in a greenhouse for germination. After five days, five seedlings (if available) per family (Appendix S1, Table S1) were planted into square pots of 11 cm x 11 cm x 12 cm filled with a 3:1 mixture of low-nutrient soil (Substrat 1, Klasmann-Deilmann GmbH, Geeste, Germany) and sand. The plants were randomly placed outdoors in a common garden of the municipal park service of the city of Luxembourg. Plants were watered when necessary and re-randomized several times. Measurements of quantitative traits — In July 2016, we recorded which of the initially 3207 plants had survived and recorded the following traits for each plant: number of leaves, diameter of the rosettes, and the width of the terminal leaflet of the longest basal leaf. We measured leaf chlorophyll content with a chlorophyll meter (SPAD-502 Plus, Minolta, Osaka, Japan) and transformed the values into chlorophyll concentrations using the formula for total chlorophyll content given by Richardson et al. (2002). In June 2017, we recorded the following traits for the 1043 surviving plants: height of the tallest flowering stem, date of opening of the first flower (flowering onset), number of stems, total number of flowerheads and the number of flowerheads with open flowers. We collected the highest cauline leaf of each plant, placed those leaves between wet paper towels in labelled envelopes in plastic bags and stored them at 5 °C. On the next day, the leaves were weighed to determine their fresh weight, placed in separate paper envelopes, pressed, and dried with silica gel. We weighed the dried leaves and scanned them at a resolution of 300 x 300 dpi together with a length standard. With the program ImageJ v. 1.51j8 (Schneider et al. 2012) we measured the area of the cauline leaves and calculated specific leaf area (SLA) as the ratio between leaf area and dry mass. Leaf dry-matter content (LDMC) was calculated as the ratio between dry and fresh weight. As a proxy for flowering phenology we calculated the proportion of heads flowering per population as the ratio between the sum of flowerheads with open flowers and the total number of flowerheads. Survival was calculated as the number of plants that survived per population divided by the total number of seedlings planted per population. Pollination experiments — In June 2017, selfing-ability was tested on a subset of 223 plants from 27 populations. On each plant, an immature flowerhead was selected. One flower per flowerhead was marked with a permanent marker and the flowerhead protected by a bag of fine nylon mesh (mesh size ca. 0.1 mm) against pollinators. Once the flowers had opened, each flower was either left as a control for autonomous self-pollination or hand-pollinated with pollen from the same flowerhead by using a toothpick to gently transfer pollen to the receptive stigma. In August of the same year, the marked flowers were collected and the presence of developed seeds was determined. # Clinal variation in quantitative traits but not in evolutionary potential along elevational and latitudinal gradients in the widespread *Anthyllis vulneraria* [https://doi.org/10.5061/dryad.gxd2547tq](https://doi.org/10.5061/dryad.gxd2547tq) This dataset contains files with measurements of plants of *Anthyllis vulneraria* from different populations studied along elevational and latitudinal gradients and of plants grown in a common garden from seeds of the initially measured plants. This dataset contains 3 files: * Quanti_indiv.xlsx is a table with measurements of quantitative traits recorded from individual *A. vulneraria* plants of different origins grown in a common garden. * Quanti_pop.xlsx is a table with population means of measurements recorded on plants of different populations in their sites of origin and variables (e.g. latitude, longitude, ...) related to the field populations. * SelfingAbility.xlsx is a table with the results from a pollination experiment to test for selfing ability. ## Description of the data and file structure ### Quanti\_indiv.xlsx * PopulationName: Name of the population of origin * MotherNumber: Number of the mother plant sampled in each population * PlantNumber: Number of the plant obtained from seeds from each mother plant in each population * Gradient: Plant sampled in a population along the elevational or latitudinal gradient * No.ofLeaves: Count of leaves * RosetteDiameter: Diameter of the rosette (in cm) * LeafletWidth: Width of the longest leaflet (in cm) * ChlorophyllContent_Transformed: Chlorophyll content measured with a chlorophyll meter (SPAD-502 Plus, Minolta, Osaka, Japan) and then transformed into chlorophyll concentrations using the formula for total chlorophyll content given by Richardson et al. (2002) (in mg/m2) * Height: Height of the plant (in cm) * FloweringOnset_Days: Date of opening of the first flower (in days) * No.ofStems: Count of stems * No.ofFlowerheads: Count of flowerheads * No.ofOpenFlowerheads: Count of flowerheads with open flowers * SLA_CaulineLeaf: specific leaf area (SLA) of the highest cauline leaf calculated as the ratio between leaf area and dry mass (in cm2/g) * LDMC_CaulineLeaf: Leaf dry-matter content (LDMC) calculated as the ratio between dry and fresh weight (in %) * SurvivalUntilSecondSummer: if a plant survived (1=yes and 0=no) until the second set of measurements Empty cells represent not available measurements at the date of data collection (due to plants not having survived or the traits not being measurable). ### Quanti\_pop.xlsx * PopulationName: Name of the sampled population * Gradient: Population sampled along the elevational or latitudinal gradient * Elevation: Elevation at the site of origin of the population (in meters above sea level) * Latitude: Latitude at the site of origin of the population (in °N) * Longitude: Latitude at the site of origin of the population (in °E) * AnnualMeanTemperature: Annual mean temperatures for the site of origin (in °C) * uHe: molecular genetic diversity derived from microsatellite analyses * Height_MotherPlants: Height of the mother plant (in cm) * RosetteDiameter_MotherPlants: Diameter of the rosette of the mother plant (in cm) * LeafletWidth_MotherPlants: Width of the longest leaflet of the mother plant (in cm) * No.ofFlowerheads_MotherPlants: Count of flowerheads of the mother plant * No.ofStems_MotherPlants: Count of stems of the mother plant * SeedMass_MeanPerMotherPlants: Average of seed mass per mother plants (in mg) Empty cells represent not available measurements. ### SelfingAbility.xlsx * PopulationName: Name of the sampled population * Gradient: Population sampled along the elevational or latitudinal gradient * SumOfSeedsSet: sum of flowers per population that developed seeds * SumOfSeedsFailedToSet: sum of flowers per population that failed to developed seeds ## Sharing/Access information Data was derived from the following sources: * Annual mean temperatures for the sites of the *A. vulneraria* populations was derived from WorldClim-database v. 2.0 (Fick and Hijmans 2017) in a 30 arc-seconds resolution (1 km2). Premise of the study Strong elevational and latitudinal gradients allow the study of genetic differentiation in response to similar environmental changes. However, it is uncertain whether the environmental changes along the two types of gradients result in similar genetically based changes in quantitative traits. Peripheral arctic and alpine populations are thought to have a lower evolutionary potential than more central ones. Methods We studied quantitative traits of the widespread Anthyllis vulneraria in a common garden. Plants originated from 20 populations along a 2000 m elevational gradient from the lowlands to the elevational limit of the species in the Alps, and from 20 populations along a 2400 km latitudinal gradient from the centre of the distribution of the species in Central Europe to its northern distributional margin. Key results Several traits showed similar clinal variation with elevation and latitude of origin. Higher QST-values than FST-values in some traits indicated divergent selection. The same traits were subject to strongly diversifying selection among populations (high QST) and strong stabilising selection within populations (low evolvability). Genetic diversity of most quantitative traits and neutral molecular markers was only weakly correlated. Plasticity in response to benign conditions declined with both increasing elevation and latitude of origin, but the evolvability of most traits did not. Conclusions The clinal variation suggests adaptive differentiation of quantitative traits along the two gradients. Our results indicate that the evolutionary potential of peripheral populations is not necessarily reduced. However, lower plasticity may threaten their survival under rapidly changing climatic conditions.

# Can niche plasticity mediate species persistence under ocean acidification? [https://doi.org/10.5061/dryad.x0k6djhtq](https://doi.org/10.5061/dryad.x0k6djhtq) This dataset originates from a study investigating the impact of ocean acidification on a temperate rocky reef fish assemblage using natural CO2 vents as analogues. The dataset covers various niche dimensions, including trophic, habitat, and behavioural niches. The study focused on how fish niches are modified in response to ocean acidification, assessing changes in breadth, shift, and overlap with other species between the acidified site and the control site. ## Description of the data and file structure #### Raw\_single\_niche\_data The “*Raw_single_niche_data*” dataset consists of seven spreadsheets, each sharing two essential columns: 'group' and 'community'. These columns are crucial for subsequent analysis using the SIBER framework. **group** = species * Common = common triplefin, *Forsterygion lapillum* * Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* * Blue_eyed = blue-eyed triplefin, *Notoclinops segmentatus* * Blenny = crested blenny, *Parablennius laticlavius* **community** = treatment * C = control * V = CO2 vents **Description of the seven spreadsheets:** 1. **Isotopes -** the dataset includes ratios of 13C/12C and 15N/14N expressed in the conventional δ notation as parts per thousand deviation from international standards. Stable isotopes were derived from a total of 251 fishes collected across three years of sampling. iso1= δ13C iso2= δ15N 2. **Stomach volumetric** - The dataset includes estimated volumetric measures of stomach contents, where the volume contribution of each prey category relative to the total stomach content (100%) was visually estimated. Data were collected between 2018 and 2019. The stomach content was analysed with this method for common triplefin, Yaldwyn's triplefin, blue eyed triplefin and crested blenny. There are 19 prey categories. 3. **Stomach count** - All prey items were counted in 10 prey categories: copepods, ostracods, polychaetes, amphipods, gastropods, bivalves, tanaids, mites, isopods , and others. Digested items that were not identifiable were excluded from the analysis. The stomach content was analysed with this method for common triplefin, Yaldwyn's triplefin and blue eyed triplefin. 4. **Stomach biomass -** The dataset includes calculated biomass derived from the mass of prey subsamples within each category, multiplied by their count. 5. **Habitat** - The microhabitat occupied and habitat orientation (horizontal, angled and vertical) was recorded using free roaming visual surveys on SCUBA (February 2018). *Microhabitat types:* t. = turf algae <10 cm in height ca. = erect calcareous algae cca. = crustose coralline algae b. = bare rocky substratum sp. = encrusting fleshy green algae cobble. = cobbles (~0.5–2 cm in diameter) *Type of surface orientation:* hor = horizontal angle = angled vert = vertical 6. **Behaviour** - Behavioural variables quantified from underwater footage and expressed as rates per minute. The behaviours are: swimming, jumping, feeding, attacking and fleeing from an attack. 7. **Aquarium**: Data from an aquarium experiment involving *Forsterygion lapillum and Notoclinops yaldwyni*, showing the proportion of time spent in available habitat types to assess habitat preference in controlled conditions. Time in each habitat type and spent in activity was derived from video recordings of 10 minutes and expressed as a proportion of total observation time. Common = common triplefin, *Forsterygion lapillum* Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* Common.c = common triplefin in presence of Yaldwyn’s triplefin Yaldwyn.c = Yaldwyn’s triplefin in presence of common triplefin turf.horizontal = time spent on horizontal turf substratum bare.horizontal = time spent on horizontal bare substratum turf.vertical = time spent on vertical turf substratum bottom = time spent on the bottom of the tank swimming = time spent swimming aquarium.wall = time spent on the walls of the tank switches = numbers of changes between habitats #### Unified\_overlap\_dataset The *“Unified_overlap_dataset”* consists of ten spreadsheets, each sharing “id”, “year”, “location” and “species “column (with few exceptions detailed). These first columns need to be factors for analysis using the Unified overlap framework. We used the R scripts provided in the original study ([Geange et al, 2011](https://doi.org/10.1111/j.2041-210X.2010.00070.x)), as detailed in the manuscript. Data for control and vents are in separate data sheets, with C = control and V = vent. **Id**: sample number **Year:** year the data were collected **Location:** North (n) or South (s), site location **Species**: fish species * Common = common triplefin, *Forsterygion lapillum* * Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* * Blue_eyed = blue-eyed triplefin, *Notoclinops segmentatus* * Blenny = crested blenny, *Parablennius laticlavius* We used the same data as per previous section. **Isotopes C and Isotopes V:** * iso1= δ13C * iso2= δ15N **Diet V and Diet C:** For **stomach content**: we used only volumetric stomach content data as inclusive of all species of interest. It is not raw data, but we used the reduced dimension obtained from nonmetric multidimensional scaling (nMDS), thus the 2 columns resulting from this analysis are vol1 and vol2. Raw data are in the datasheet **Stomach volumetric** in the “*Raw_single_niche_data*” dataset. **Habitat association C and Habitat association V** / **Habitat - C and Habitat - V** For **Habitat association**, the columns are id, species, habitat and position. The habitat association for each species is categorical based on habitat occupied and position (e.g., turf - vertical). Information for Crested blenny were extracted from the behavioural video recordings (with each video being a replicate). The dataset is then linked to **Habitat cover** in both control (C) and vent (V) sites to determine the choice of the habitat based on habitat availability. Therefore, the habitat cover only presents the percentage cover of each habitat type at control and vent. *Habitat:* turf = turf algae <10 cm in height ca = erect calcareous algae cca = crustose coralline algae barren = bare rocky substratum sp = encrusting fleshy green algae cobble = cobbles (~0.5–2 cm in diameter) sand = sand *Position:* hor = horizontal angle = angled vert = vertical **Behaviour C and Behaviour V**: Behavioural variables quantified from underwater footage and expressed as rates per minute. The behaviours are: swimming, jumping, feeding, attacking and fleeing from an attack. Reference: Geange, S. W., Pledger, S., Burns, K. C., & Shima, J. S. (2011). A unified analysis of niche overlap incorporating data of different types. *Methods in Ecology and Evolution*, 2(2), 175-184. [https://doi.org/10.1111/j.2041-210X.2010.00070.x](https://doi.org/10.1111/j.2041-210X.2010.00070.x) We used a small hand net and a mixture of ethanol and clove oil to collect the four species of interest (Forsterygion lapillum, Notoclinops yaldwyni, Notoclinops segmentatus and Parablennius laticlavius) at both control and vent sites over four years. For stable isotope analysis, white muscle tissue was extracted from each fish and oven-dried at 60 °C. The dried tissue was subsequently ground using a ball mill. Powdered muscle tissue from each fish was individually weighed into tin capsules and analysed for stable δ 15N and δ13C isotopes. Samples were combusted in an elemental analyser (EuroVector, EuroEA) coupled to a mass spectrometer (Nu Instruments Horizon) at the University of Adelaide. We then analysed the isotopic niche in SIBER. For stomach content analysis the entire gut was extracted from each fish. Using a stereomicroscope, for count and biomass, all prey items in the stomach were counted first. For each prey category, well-preserved individuals were photographed and their mass was calculated based on length and width. The average mass per individual for each category was then multiplied by the count to determine total prey biomass. For the volumetric method, the volume contribution of each prey category relative to the total stomach content was visually estimated (algae were accounted for). Digested items that were not identifiable were excluded from the analysis. Each stomach content dataset was reduced to two dimensions with non-metric multidimensional scaling (nMDS) to be then analysed in SIBER. To assess habitat choice, visual surveys were conducted on SCUBA, to record the microhabitat type and orientation occupied by Forsterygion lapillum, Notoclinops yaldwyni and Notoclinops segmentatus. The resulting dataset comprised a total of 17 distinct combinations of habitat types and surface orientations. The dataset was simplified to two dimensions using correspondence analysis (CA) for subsequent SIBER analysis. Fish behaviour was assessed using GoPro cameras both in situ and during controlled aquarium experiments. In the field, recordings lasted 30 minutes across 4 days, with analysis conducted using VLC. Initial acclimation and periodic intervals (10 minutes every 5 minutes) were excluded from analysis. In controlled aquarium settings, individuals of Forsterygion lapillum and Notoclinops yaldwyni were observed both in isolation and paired. Their habitat preference, surface orientation, and activity levels were recorded for 10 minutes to assess behaviour independent of external influences. Both datasets were dimensionally reduced for analysis in SIBER: non-metric multidimensional scaling (nMDS) was applied to the in situ behavioral data, while principal component analysis (PCA) was used for the aquarium experiments. Unified analysis of niche overlap We quantified the local realised niche space for each fish species at control and vent along the four niche classes, adapting the data as follows: isotopes (continuous data): raw data. stomach content (continuous data): reduced dimension from the volumetric measure of the previous step. habitat association (elective score): habitat and orientation preference linked to Manly’s Alpha association matrix. behaviour (continuous data): raw data. Global change stressors can modify ecological niches of species, and hence alter ecological interactions within communities and food webs. Yet, some species might take advantage of a fast-changing environment, and allow species with high niche plasticity to thrive under climate change. We used natural CO2 vents to test the effects of ocean acidification on niche modifications of a temperate rocky reef fish assemblage. We quantified three ecological niche traits (overlap, shift, and breadth) across three key niche dimensions (trophic, habitat, and behavioural). Only one species increased its niche width along multiple niche dimensions (trophic and behavioural), shifted its niche in the remaining (habitat), and was the only species to experience a highly increased density (i.e. doubling) at vents. The other three species that showed slightly increased or declining densities at vents only displayed a niche width increase in one (habitat niche) out of seven niche metrics considered. This niche modification was likely in response to habitat simplification (transition to a system dominated by turf algae) under ocean acidification. We further show that at the vents, the less abundant fishes have a negligible competitive impact on the most abundant and common species. Hence, this species appears to expand its niche space overlapping with other species, consequently leading to lower abundances of the latter under elevated CO2. We conclude that niche plasticity across multiple dimensions could be a potential adaptation in fishes to benefit from a changing environment in a high-CO2 world. 

Baseline and future (2036-2065) river water levels and discharges at 4 gauging stations along the Cambodian Mekong (Kratie, Kampong Cham, Chrouy Changva, and Neak Loeung) under different scenarios of climate change (RCP 4.5 and 8.5) and infrastructural developments. Average depth and duration flood maps are also included for each scenario. A full description of the methods and results can be found in the article: Alexander J. Horton, Nguyen V. K. Triet, Long P. Hoang, Sokchhay Heng, Panha Hok, Sarit Chung, Jorma Koponen, and Matti Kummu. (2022). The Cambodian Mekong floodplain under future development plans and climate change. Nat. Hazards Earth Syst. Sci.

Here the processed experimental data of the accepted paper given below is documented and made available: Berger, F., Neuhaus, L., Onnen, D., Hölling, M., Schepers, G., and Kühn, M.: Experimental analysis of the dynamic inflow effect due to coherent gusts, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2022-2, accepted, 2022.