These data were collected to study oxidative weathering processes in the Waiapu River catchment, New Zealand, with potential carbon release sourced from the oxidation of petrogenic organic carbon or carbonate dissolution coupled to the oxidation of sulfide minerals. There, in mudstones exposed in a highly erosive gully complex, in situ CO2 emissions were measured with drilled gas accumulation chambers following the design by Soulet et al. (2018, Biogeosciences 15, 4087-4102, https://doi.org/10.5194/bg-15-4087-2018). Temporal and spatial variability in CO2 flux can be put in context with environmental changes (e.g., temperature and hydrology). For this, CO2 release from 5 different chambers, which were installed over a transect of ~ 10 m length in a gully above a nearby streambed, was measured several times over a short study period (circa one week). In addition, the gaseous CO2 storage (partial pressure) in the shallow weathering zone was measured prior to a CO2 flux measurement. To understand the source of CO2, gas samples were collected and their stable and radioactive carbon isotope compositions determined. In this process, we identified a contaminant, which was associated with the chamber installation, that can be traced in the gas samples that were collected within 4 days following the installation. Details of the subsequent data analysis and interpretation can be found in: Roylands et al. 2022, Chemical Geology: Capturing the short-term variability of carbon dioxide emissions from sedimentary rock weathering in a remote mountainous catchment, New Zealand. This work was supported by the European Research Council (Starting Grant to Robert G. Hilton, ROC-CO2 project, grant 678779).

A set of six large catalogues documenting the seismic sequence that occurred in central Italy between 2016 and 2017, characterized by a cascade of four MW5.5–6.5 events. The earthquake catalogues possess different levels of resolution and completeness that result from progressive enhancements in both detection sensitivity and hypocentral location determination. These quality differences reflect the subsequent application of advanced methods.

This dataset contains results from nanoindentation testing of five shale samples from the Horn River Basin (core from wells A100B/94 and D94A/94). The samples are from the following formations: A3 Fort Simpson, A6 Fort Simpson, D1 Muskwa, A16 Otter Park, and A20 Evie. The data is in two sets. Set 1 includes nanoindentation data from all samples, with grids conducted both parallel and perpendicular to the bedding plane. In Set 2, additional chemical analysis of select grids (on samples A3, A6 and A20) was undertaken using SEM/EDS. Both sets include the following tab-separated .txt files: grid_para.txt [Load-displacement-time data for each indent (parallel indentation)]; grid_para_summary.txt [Reduced elastic modulus, hardness and creep modulus for each indent (parallel indentation)]; grid_perp.txt [Load-displacement-time data for each indent (perpendicular indentation)]; grid_perp_summary.txt [Reduced elastic modulus, hardness and creep modulus data for each indent (parallel indentation)]. Set 2 also includes .tif files containing SEM images and EDS chemical analysis of the grids. The data has been filtered to remove indents which show 'pop-in' behaviour or time-displacement curves that do not conform to a logarithmic fit. ACKNOWLEDGMENT - The authors wish to thank the Natural Environment Research Council (NERC) for funding this research through the SHAPE-UK project (grant numbers NE/R018057/1, NE/R017840/1, and NE/R017565/1), which forms Challenge 3 of the UKUH (Unconventional Hydrocarbons in the UK Energy System) programme.

The data consists of estimated hourly average inflow discharge (m3s-1) and water temperature (°C) of the inflow of the inner basin of Elterwater (lat: 54.428, long: -3.034) from January 2012 to December 2019. The work was supported by the Natural Environment Research Council (Grant NE/ L002604/1). Full details about this dataset can be found at https://doi.org/10.5285/2883aaf1-6148-49cb-904a-d271a028c716

This dataset includes a set of modelled outputs produced as part of the DECIDE project. Three groups were modelled; butterflies, day-flying moths and night-flying moths. (For the moths, we only considered 'macro-moths'.) For each group there are three outputs; species richness, model variability and DECIDE recording priority. The outputs summarise across multiple species within each group. The model’s prediction probability of occurrence for individual species is not made available. The outputs are in a raster format on Ordnance Survey National Grid reference system (OSGB) at 100m x 100m resolution. Species richness layers are a modelled prediction of how many species are present at a location. Model variability is used to determine where a model is uncertain about its prediction of species occurrence. Model variability is combined with information about how recently a species had been recorded to produce the DECIDE recording priority. The DECIDE recording priority is a measure to prioritise locations to support adaptive sampling of where to collect species occurrence data to improve species distribution models. Full details about this dataset can be found at https://doi.org/10.5285/445381ce-f412-48a0-bc3c-2d0ef4737274

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset provides Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 1x1 kilometres (km) grid squares of the UK averaged over the years 2018 to 2020. The data consist of deposition values for sulphur, oxidised nitrogen and reduced nitrogen, and base cations. Total deposition is the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. Habitat-specific data are provided for (i) moorland/short vegetation everywhere, and (ii) forest everywhere. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also calculated. The habitat-specific data are recommended for use with critical loads for the calculation of critical load exceedances. The work in generating and compiling the dataset has been funded by the UK Centre for Ecology & Hydrology (UKCEH) and various Departments for Environment, Food & Rural Affairs (Defra) contracts. Full details about this dataset can be found at https://doi.org/10.5285/4a5a9140-96f1-4aee-b547-ef570238fdbd

The data represent a quantitative measure of aboveground (vegetation) biomass, organic carbon content and aboveground (vegetation) carbon from 144 vegetation samples collected across ten UK saltmarshes between 2019 and 2020. Sites were chosen to represent contrasting habitat types in the United Kingdom, in particular sediment types, vegetation, and sea level history. Full details about this dataset can be found at https://doi.org/10.5285/f71c9f3e-0ae1-4318-a3ea-1dd30b7af3be

Bulk elemental (carbon and nitrogen) and stable isotope (delta 13C and delta 15N) data produced from 491 samples collected between 2016-2021 from terrestrial (soil, peat, living biomass, dead biomass), intertidal (saltmarsh vegetation, saltmarsh roots, seagrass biomass, mudflat, faecal matter) and marine (macroalgae, microalgae zooplankton, finfish aquaculture waste) environments across the UK. These samples alongside analytical standard derived from natural materials (lignin, humic acid, cellulose, glucose, protein) were analysed to determine their bulk elemental (organic carbon and nitrogen) and stable isotope (delta 13C org and delta 15N) composition. These values are envisioned to be used to constrain organic carbon sources (terrestrial vs marine) in the natural environment when used alongside isotope mixing models. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/a445a7a8-528d-4e0b-9094-28cbcd449367

The data set contains grain size distributions, organic matter (OM) content and trace metal distribution (including Fe, Zn, Cu, Cr and Pb) of 37 shallow cores of sediments sampled from dams across the Limpopo River Basin. The dams include: Gaborone, Lotsane and Shashe dams in Botswana; Houtrivier, Nwanedi and Mutshedzi dams in South Africa; Ripple Creek and Zhovhe dams in Zimbabwe; and Massingir Dam in Mozambique. Data from two cores sampled from an oxbow lake in Mozambique are also included. The cores were collected with a gravity corer using PVC pipes of 5 cm diameter by a team from Botswana International University of Science and Technology (BIUST) led by Dr. Franchi between July 2018 and April 2021. Full details about this dataset can be found at https://doi.org/10.5285/b8db8239-3bde-454a-aa75-d1cec24c8763

This dataset provides the projections of meteorological, hydrological, and agricultural droughts for the near-future period (2021-2050) for the Mun River basin, in Northeast Thailand. Near future drought characteristics (duration, intensity, and severity) are projected for climate change (CC) scenario using 8 CMIP6 climate models (CNRM-CM6-1, CNRM-CM6-1-HR, EC-Earth3P, EC-Earth3P-HR, HadGEM3-GC31-HH, HadGEM3-GC31-HM, HadGEM3-GC31-MM, HadGEM3-GC31-LL) for SSP5-8.5 scenario. Full details about this dataset can be found at https://doi.org/10.5285/b11c040d-c3c0-43c5-a7c0-442b067dc526