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  • Microgravity data collected at Uturuncu Volcano between March 2010 and November 2018 The file contains microgravity data collected between March 2010 and November 2018 in the Altiplano-Puna Volcanic complex.

  • This dataset contains biogeochemical and edaphic information from burned peat soil on the Stalybridge estate located near Manchester (UK), commonly referred to as Saddleworth moor. This study was conducted after a wildfire fire on the Saddleworth moor in June 2018. The sample plots included areas with deep and shallow peat burn. The data includes geographical information (location, elevation and slope), soil temperature and soil chemical composition (carbon, nitrogen and 22 other elements). The dataset is the result of research funded by a NERC Urgency grant entitled 'RECOUP-Moor: Restoring Ecosystem CarbOn Uptake of Post-fire Moorland' (NE/S011943/1, led by Dr. Bjorn Robroek of the University of Southampton (now Radboud University Nijmegen, the Netherlands). Full details about this dataset can be found at https://doi.org/10.5285/1fa8d605-b996-4687-ace2-1fa59cd5c6dd

  • Phenotypes (growth and phenology) for Scots pine trees in a long-term common garden trial planted in three sites in Scotland, surveyed annually from 2013 to 2020. Full details about this dataset can be found at https://doi.org/10.5285/1c9367fb-ea87-47a1-8257-d9fed54215e7

  • This is a theoretical model of leadership in warfare by exploitative individuals who reap the benefits of conflict while avoiding the costs. In this model we extend the classic hawk-dove model to consider pairwise interactions between groups in which a randomly chosen leader decides whether the group will collectively adopt aggressive or peaceful tactics. We allow for unequal sharing of fitness payoffs among group members such that the leader can obtain either a larger share of the benefits, or pay a reduced share of costs, from fighting compared to their followers. Our model shows that leadership of this kind can explain the evolution of severe collective violence in certain animal societies. Full details about this application can be found at https://doi.org/10.5285/7aab999e-cef9-41c2-8400-63f10af798ec

  • This dataset is a compilation of results obtained from vegetation surveys in the Stalybride estate moorlands (commonly known as the Saddleworth moors) following a wildfire in 2018. Ten plots were established in October 2018 at the post-fire site which were 10 m x 10 m in size. Five plots were identified as suffering a less severe (shallow) burn. The other 5 plots were in areas where a more severe (deep) burn. In all plots the surface vegetation had been removed by the fire exposing the bare peat. The data file contains: (1) On-site post-fire vegetation data – species ID and coverage, and (2) species presence in the one-year post-fire seed bank. The dataset is the result of research in the light of an NERC Urgency grant entitled 'RECOUP-Moor: Restoring Ecosystem CarbOn Uptake of Post-fire Moorland' (NE/S011943/1, led by Dr. Bjorn Robroek of the University of Southampton (now Radboud University Nijmegen, the Netherlands). Full details about this dataset can be found at https://doi.org/10.5285/56561ed3-55d0-454c-a6b9-7e633ccf9647

  • These data are the simulated peat heights and water-table depths (both in cm) from a DigiBog run. The virtual peatland was configured as a 2-D transect of 100 x 2m x 2m columns. The data were generated for each year of a 5,100-year run. After 4,900 years, six ditches were added and the model allowed to run for a further 100 years. After this time, the ditches were ‘restored’ and the simulation continued until a total runtime of 5,100 years had elapsed. Full details about this dataset can be found at https://doi.org/10.5285/1d16b303-ca1d-43b4-93b1-c8172adc9792

  • Data comprise soil organic carbon content from a simulation using the ECOSSE model; a pool-based carbon and nitrogen turnover model. Simulations were performed using input data from the Sunjia research farm in southeast China (Jianxi province). Data here is from simulations using the global version of the ECOSSE model, a package which applies the regular model spatially. Input data for the simulations were provided by the soil science department of the Chinese Academy of Sciences. Simulations were conducted in 2018. Full details about this dataset can be found at https://doi.org/10.5285/876fa724-c3d3-4091-8de2-8140b7c973eb

  • Data were collected in 2015, 2016 and 2017 to provide Digital Surface Models (DSM) for two sections of the South Saskatchewan River, Canada. DSMs were generated using aerial plane images with a 0.06m ground resolution, captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. DSMs were generated as part of NERC project NE/L00738X/1. DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates. Full details about this dataset can be found at https://doi.org/10.5285/13695138-227f-4d85-9049-0a9cba9e1867

  • This dataset contains half-hourly output data (for the year 2011) generated by a preliminary version of the Shrubland Ecosystem Assessment (SEcA) model. SEcA calculates the ecosystem processes for a semi-arid shrubland system, for this dataset the model has been configured for a Caatinga ecosystem. The model generates four output files, those generating the aerodynamic and surface resistances, state variables, energy balance fluxes, and carbon flux-related outputs. The data provided here relate to model runs with the JULES Farquhar model, with the Sinclair plant water stress switched on. This work was funded by Newton/NERC/FAPESP Nordeste project: NE/N012488/1. Full details about this dataset can be found at https://doi.org/10.5285/ad86c0d3-624c-4ae3-9280-8d1ccbe14929

  • We examine the role of cement on compaction band formation by performing triaxial tests on three sandstones, Bentheim, Castlegate and a synthetic sandstone which possess very similar porosities (~26-29%) and grain sizes (~230-300 µm), but which are cemented differently, with syntaxial quartz overgrowths, clay, and amorphous quartz cement respectively. Each sample was taken to 5% axial strain at a starting effective stress equivalent to 85% of its hydrostatic yield (P*) value, which were identified from yield under hydrostatic loading. These data for the 3 samples are presented as matlab data files. Post-deformation, each of the 3 cores underwent backscatter SEM and subsequent image analysis to examine any localised variations in porosity and grain size. These data are presented as csv files. Discrete bands form in each of the 3 sandstones but are distributed differently across each sample. Our results suggest that cement type plays a significant role in the micromechanics of deformation within each of the sandstones, which in turn, determines where the compaction bands nucleate and develop. These results may provide a starting point to investigate the role of cement on compaction localisation further.