FWHM of coral skeletal samples from 7 coral genotypes cultured in an aquarium at seawater pCO2 of 180, 260, 400 and 750 µatm and at seawater temperature of 25 and 28 degrees C (39 samples total). Data were collected to determine how environmental conditions influence disorder in the aragonite lattice of coral skeletons. Data were collected between August 2020 and December 2022 by Phoebe Ross, Celeste Kellock, Cristina Castillo Alvarez and Nicola Allison and interpreted by Phoebe Ross, Celeste Kellock, Cristina Castillo Alvarez, David Evans, Nicola Allison, Adrian Finch, Kirsty Penkman, Roland Kröger, and Matthieu Clog.

Precipitations were conducted using a pH stat titrator using the constant composition technique between August 2020 and April 2022. Aragonite precipitation rates are estimated from the rate of titrant dosing. pH and DIC are used to estimate the seawater aragonite saturation state of each precipitation and, on occasion, the [HCO3-] and [CO32-]. Data were collected to determine how changes in the calcification fluids of calcareous organisms affect aragonite precipitation. Data were collected by Cristina Castillo Alvarez and interpreted by Cristina Castillo Alvarez, Nicola Allison, Adrian Finch, Kirsty Penkman, Roland Kröger and Matthieu Clog.

Aragonite precipitations rates of precipitations from seawater, using a pH stat titrator using the constant composition technique between September 2021 and December 2022. Aragonite precipitation rates are estimated from the rate of titrant dosing. Data were collected to determine how changes in the calcification fluids of calcareous organisms affect aragonite precipitation. Data were collected by Giacomo Gardella and Nicola Allison and interpreted by Giacomo Gardella, Cristina Castillo Alvarez, Nicola Allison, Adrian Finch, Kirsty Penkman, Roland Krӧger and Matthieu Clog.

Amino acid compositions of coral skeletons from 4 massive Porites spp. genotypes (G4, G5, G6, G7) cultured in an aquarium at seawater pCO2 of 180, 260, 400 and 750 µatm and at seawater temperature of 25 and 28°C. Protein was extracted from the skeletal samples and hydrolysed to individual amino acids. Data were collected to determine how environmental conditions influence coral skeletal biomolecules. Data were collected between August 2020 and December 2022 by Celeste Kellock, Cristina Castillo Alvarez, David Evans and Nicola Allison and interpreted by Celeste Kellock, Cristina Castillo Alvarez, David Evans, Nicola Allison, Adrian Finch, Kirsty Penkman, Roland Kröger, and Matthieu Clog.

Amino acid compositions of aragonite samples precipitated from seawater, using a pH stat titrator using the constant composition technique between September 2021 and December 2022. Samples were precipitated from 330 mL of seawater with no biomolecules (control) or with a seawater concentration of 2 mM of aspartic acid (Asp), 2 mM glycine (Gly), 2 mM of both amino acids (Asp+Gly) or 2 mM dipeptide glycyl-L-aspartic acid (Asp-Gly) or from 33 mL of seawater with variable concentrations of aspartic acid (Asp) or tetra-aspartic acid (Asp4). Protein was extracted from the samples and run as free amino acids (to detect amino acids in free form) and as hydrolysed samples (to detect peptides). Data were collected to determine how changes in the calcification fluids of calcareous organisms affect aragonite precipitation. Data were collected by Giacomo Gardella, Sam Presslee and Nicola Allison and interpreted by Giacomo Gardella, Cristina Castillo Alvarez, Nicola Allison, Adrian Finch, Kirsty Penkman, Roland Krӧger, Sam Presslee and Matthieu Clog

The research team collected data on soil-atmosphere exchange of trace gases and environmental variables during four field campaigns (two wet seasons, two dry seasons) the lowland tropical peatland forests of the Pastaza-Marañón foreland basin in Peru. The campaigns took place over a 27 month period, extending from February 2012 to May 2014. This dataset contains measurements from field sampling of soil-atmosphere fluxes concentrated on 4 dominant vegetation types in the lowland tropical peatland forests of the Pastaza-Marañón foreland basin. Vegetation types included; forested vegetation, forested [short pole] vegetation, Mauritia flexuosa-dominated palm swamp, and mixed palm swamp. They were measured at 5 different sites in Peru including; Buena Vista, Miraflores, San Jorge, Quistococha, and Charo. Greenhouse gas (GHG) fluxes were captured from both floodplain systems and nutrient-poor bogs in order to account for underlying differences in biogeochemistry that may arise from variations in hydrology. Parameters include methane and nitrous oxide fluxes, air/soil temperatures, soil pH, soil electrical conductivity, soil dissolved oxygen content, and water table depth. See documentation and data lineage for data quality. These data were collected in support of the NERC project: Amazonian peatlands - A potentially important but poorly characterised source of atmospheric methane and nitrous oxide (NE/I015469/2)

These datasets are for samples collected from Volcan de Colima (Mexico) which is at coordinates: 19°30’46" N 103°37’02" W / 19.512727°N 103.617241°W. This volcano erupts magmas that are crystal-bearing, making those cooled volcanic rocks ideal for experimentation. And so samples were cored from blocks from that volcano and those cores were then returned to high temperatures (up to 1000 C) and then deformed under controlled stresses. These data form the central part of this publication: https://doi.org/10.1016/j.jvolgeores.2024.108198. The deformation experiments were performed at LMU (Munich, Germany). The volcano coordinates from which the samples were collected are given above. The samples were deformed in a high temperature hydraulic press equipped with acoustic emission sensors. This is the ideal device for determining the behaviour of the magmas from Volcan de Colima under the same stresses and temperatures at which they were erupted. The data give key clues as to the modes of flow behaviour of the magma in volcanoes. This work provides generalised insights into magma flow behaviour.

This dataset contains experimental data supporting Vasseur et al. (2023) https://doi.org/10.1111/jace.19120, which investigates the process of glass sintering during dehydration. The experiments were conducted in 2022 at LMU (Munich, Germany) . The samples were synthetic and so were not collected at any given site but were created in the laboratory. For each experiment presented, a sample of glass powder was hydrated by exposing it to a hydrous (H2O) atmosphere at high temperature (600-700 C) for a number of hours. The glass particles were then hydrated, and this fact was checked by looking for a relative mass loss if the same powder was returned to high temperature but under a non-hydrous atmosphere; indeed, mass loss occurred as the water left the particles again. That mass loss was measured and the kinetics of mass loss were analysed. The data demonstrate that there is a quantifiable competition between the rate at which water will move into or out of particles and the rate at which particles will sinter together. This same competition is relevant to volcanic eruptions and has knock-on implications for the evolution of permeability of magmas, which is a prominent area of study for this grant. These data were collected by F. Wadsworth, analysed by J. Vasseur, and the paper was both facilitated by and written by Y. Lavallée and D. B. Dingwell. All authors were responsible for the output of the data.

These data present volume estimates from images (using the solid of revolution method from the cross-sectional area) of clasts expanding during vesiculation at high temperature. The data also contain clast interior volume estimates without the dense rind around the clasts (formed by diffusive outgassing, and estimated through time),l which is is calculated in Matlab. The methods are provided in more detail in Weaver et al., 2022. These data contain sample measurements (surface area), total clast volume calculation (using solid of revolution from clast cross-sectional area), degassed skin area (using imerode in Matlab and the diffusion data provided in the table) and skin volume (solid of revolution from skin surface area), and core surface area and volume from the difference between total clast and skin volumes/skin area. All data are presented in Weaver et al., 2022 (https://doi.org/10.1016/j.jvolgeores.2022.107550), where further details of the methods can also be found. All data were collected and analysed at the University of Liverpool using clasts from Hrafntinnuhryggur, Iceland. The geographical location of the samples collected is of no relevance to this study, as the samples were selected for their physical attributes. All data were collected and analysed throughout 2021 and 2022. Volcanic glass cylinders of different starting sizes were placed in a furnace at high temperature (1006 oC). Two furnaces were used, either a tube furnace with open ends to allow imaging of the sample silhouette, or a box furnace with a sapphire window to allow imaging of the sample as vesiculation takes place. Cross-sectional areas are then converted to volumes using solid of revolution as vesiculation is isotropic. Diffusion modelling is used to quantify the development of the fully degassed rind around the sample and used to estimate the rind volume through imerode in Matlab and solid of revolution. Total clast, core and rind volumes are thus able to be retrieved. As magmas approach the surface of the Earth, volatile saturation in the melt decreases, which results in volatile exsolution in vesicles (vesiculation) and outgassing. The interplay between the amount of vesicles trapped in the melt and those that diffusively outgas from the surface is dependent on the volume to surface area ratio. Understanding the kinetics of outgassing and vesiculation is key to understand pressure build-up in magmatic conduits and effusive-explosive transitions at volcanoes.

We collected major element, trace element and Nd isotopes of cumulate plagioclase and clinopyroxene in lower crustal gabbros from Hess Deep oceanic crust (~2°15'N, 101°30'W) to investigate the Nd isotopic heterogeneity of melts delivered to a complete section of Hess Deep oceanic crust, accreted at the fast-spreading (133 mm/yr) East Pacific Rise (EPR). These data are presented in Cooper et al. (2025) (https://doi.org/10.1130/G52872.1). Elemental maps of 58 samples were initially obtained prior to selecting a subset of 25 samples for in-situ microanalysis. We targeted the Nd isotope record of cumulate plagioclase and clinopyroxene from lower crustal gabbro samples, representing early crystallisation products of melts delivered to the crust. These samples were collected in several expeditions: Ocean Drilling Program (ODP) Leg 147; RSS James Cook cruise JC21; Integrated Ocean Drilling Program (IODP) Expedition 345 (Site U). Combined, these studies provide the most complete composite section of fast-spreading EPR crust to date (stratigraphic depth of 4350 m to 25 m). In our study, we selected 25 samples for in situ Nd isotope microanalysis, covering the range of mineralogy and textural diversity, and over the full stratigraphic depth. For a comparison to local MORB compositions, we selected a set of 13 upper-crustal sheeted dikes collected on the RSS James Cook cruise JC21. Our data reveal that the mantle is heterogeneous at the scale of melt extraction, and the crystal record from the lower crust shows greater 143Nd/144Nd heterogeneity than the overlying MORB. Hence, Pacific MORBs do not reflect the full heterogeneity of their mantle source, and some aggregation of melts occurs within the crust. Data was collected between 2020 and 2023 by George Cooper, Johan Lissenberg and Max Jansen at Cardiff University, UK, as part of NERC Grant NE/T000317/1:HiDe: A Highly Heterogeneous Depleted Upper Mantle? Mineral isotopic analyses were performed on a Thermo Scientific TRITON Plus at the Vrije Universiteit in Amsterdam. The long-term average and reproducibility (2019–2022) for the JNdi-1 standard is 0.512094 ± 0.000011 2 SD (standard deviation; n = 28) with 1011Ω resistors (used for clinopyroxene) and 0.512105 ± 0.000044 2 SD (n = 45) with four 1013Ω resistors (used for plagioclase). Full methodology can be found within the supplemental Material of Cooper et al. (2025) at https://doi.org/10.1130/GEOL.S.28485770 The DOI is a supplement to https://doi.org/10.1130/G52872.1 Methodology: https://gsapubs.figshare.com/articles/journal_contribution/Supplemental_Material_Crustal_versus_mantle-level_aggregation_of_heterogeneous_melts_at_mid-ocean_ridges/28485770?file=52665137