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  • This data set contains stacked detection matrices for 28 recorded mammal species across 115 sampling locations at the Stability of Altered Forest Ecosystems (SAFE) project site located in Sabah, Malaysian Borneo. Information for each camera trap sampling location, including spatial information and sampling effort is included. Data were collected in order to determine the contribution of carbon-based policies to biodiversity conservation in agricultural land-use mosaics. These data are essential to the development of the occupancy detection matrix. Data were collected in 2015 during a project which was included in the NERC Human-modified tropical forest (HMTF) Programme. Full details about this dataset can be found at https://doi.org/10.5285/62774180-ae72-4873-9482-e8be3935f533

  • WCRP CMIP5: The CNRM-CERFACS team CNRM-CM5 model output collection.The CNRM-CERFACS team consisted of the following agencies: Centre National de Recherches Meteorologiques (CNRM) and Centre Europeen de Recherche et Formation Avancees en Calcul Scientifique (CERFACS).

  • Collection of data produced by the GAUGE (Greenhouse gAs Uk and Global Emissions) Project. The GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology. GAUGE was part of the Greenhouse Gas Emissions and Feedback Programme funded by the Natural Environment Research Council (NERC).

  • The Fontaine Ardente (FA) and Rochasson (ROC) natural gas seepage sites are located southwest (FA) and east (ROC) of Grenoble, France. For both field sites, gas is thought to originate from buried Middle Jurassic mudstones and argillaceous limestones and thought to migrate upward along small faults. At FA, the site located along a small seepage close to the river bed of a small creek. The gas seepage site at ROC is located along the flank of a thalweg and is linked to a small landslide in clayey horizons. New methane clumped isotope data is correlated to previously published data by Gal et al (2017) and recent isotopic data acquired within SECURe deliverable 3.4. During October 2019, 5 samples were collected from the FA and ROC sites and the following analyses were conducted: - Gas composition (C1-C5, CO2, N2, H2S, Ar) and and stable isotope analyses (methane δ13C and δD, CO2 δ13C, δ15N) - Methane clumped isotope analyses (Δ13CD and ΔDD) The dataset was created within SECURe project (Subsurface Evaluation of CCS and Unconventional Risks) - https://www.securegeoenergy.eu/. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 764531

  • The R code "carbon_stock_calculations.R" estimates aboveground carbon stocks for 49 plots in 14 fragmented forest sites and 4 continuous forest sites in Sabah, Malaysian Borneo, using the vegetation dataset 'Vegetation and habitat data for fragmented and continuous forest sites in Sabah, Malaysian Borneo, 2017'. The 14 fragmented sites were all in Roundtable on Sustainable Palm Oil-certified oil palm plantations, and are hereafter termed 'conservation set-asides'. The code also estimates the aboveground carbon stocks of oil palm plantations for comparison. The R code "analyses_and_figures.R" runs analyses and makes figures of aboveground carbon stocks and associated plant diversity for these sites, as presented in Fleiss et al. (2020) This R code was created in order to investigate the following: (1) to establish the value of conservation set-asides for increasing oil palm plantation aboveground carbon stocks; (2) to establish whether set-asides with high aboveground carbon stocks can have co-benefits for plant diversity; (3) to compare the carbon stocks and vegetation structure of conservation set-asides with that of continuous forest, including assessing tree regeneration potential by examining variation in seedling density; (4) to examine potential drivers of variation in aboveground carbon stocks of conservation set-asides (topography, degree of fragmentation, and soil parameters); (5) to scale-up the estimates of the aboveground carbon stocks of conservation set-asides, in order to predict average carbon stocks of oil palm plantations with and without set-asides, and for varying coverage of set-asides across the plantation. Full details about this application can be found at https://doi.org/10.5285/9ff5cdca-b504-4994-8b07-5912ee6aff47

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains soil respiration data from the Climoor fieldsite in Clocaenog forest, north-east Wales. Measurements began in March 1999 at the field site, and were repeated in approximately bi-weekly intervals until Oct 2013 (although there are some larger gaps for technical or logistical reasons in this 14 year dataset). The data were collected using 3 different methods/machines over the years: static chambers, soil respiration chamber and EGM-4 (from PP Systems), and soil respiration chamber and Li8100 (from Licor Biosciences). The method used is detailed in the data and described further in the supporting documentation. Full details about this dataset can be found at https://doi.org/10.5285/49a26df5-6b50-41f2-8d3a-c235eedc5cd1

  • This dataset contains measurements of herbivory and the potential controls on herbivory for nitrogen-fixing and non-fixing trees in a mature tropical forest of Panama. Data include herbivory measures on 1,626 leaves from 350 seedlings belonging to 43 species, 23 nitrogen-fixing species, 20 non-fixing species. Herbivory metrics are presented at the leaf and seedling level. The data also includes leaf chemical and physical traits hypothesized to influence herbivory at the species level, and seedling-level traits such as stem length and growth rate. Data were collected in 2017 by measuring leaf area missing on seedlings in the BCI 50 ha plot seedling census in order to determine whether fixers have higher rates of herbivory than non-fixers, and what traits govern herbivory. Data were collected by W. Barker, S.J. Wright, L. Comita, B. Sedio and colleagues. Funders of research generating the data include the Natural Environment Research Council, U.S. National Science Foundation, Leverhulme Trust, British Council, Society of Experimental Biology Company of Biologists, University of Leeds Priestly International Centre for Climate and Smithsonian Tropical Research Institute Full details about this dataset can be found at https://doi.org/10.5285/67c95112-edee-435f-9355-9d8bab3a5634

  • This dataset consists of stock (area) data for landscape features across Great Britain in 1984. Data are presented as areas of Broad (or Priority) Habitats, with associated landscape attributes (such as plant species and land use), within a set of 379 1km squares across Great Britain. The Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 by the Centre for Ecology & Hydrology, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to habitat areas, vegetation species data, soil data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey. Full details about this dataset can be found at https://doi.org/10.5285/b656bb43-448d-4b2c-aade-7993aa243ea3

  • This datasets contains a box model of the atmosphere‐ocean to understand surface warming response and explain how surface warming varies in time with carbon emissions. The box model consists of three homogeneous layers: a well‐mixed atmosphere, an ocean mixed layer with 100‐m thickness, and an ocean interior with 3,900‐m thickness, all assumed to have the same horizontal area. The model solves for the heat and carbon exchange between these layers, including physical and chemical transfers, but ignoring biological transfers, and sediment and weathering interactions. The model is forced from an equilibrium by carbon emitted into the atmosphere with a constant rate of 20 PgC/year for 100 years and integrated for 1,000 years. Ocean ventilation is represented by the ocean interior taking up the heat and carbon properties of the mixed layer on an e-folding time scale of 200 years. The model was generated as part of Natural Environment Research Council (NERC) Discovery Science project “Mechanistic controls of surface warming by ocean heat and carbon uptake” standard grant reference NE/N009789/1 lead by Principal Investigator Professor Ric Williams.Model code and associated metadata are held in the archives at the British Oceanographic Data Centre. Other datasets generated by this grant are discoverable via EDMED 6712.

  • The data comprises GIS layers representing the permeability of artificial deposits for Great Britain. The permeability data has been derived from DiGMap-GB (Digital Geological Map Data of Great Britain), and therefore reflects the scale of DiGMap-GB. For the majority of the Great Britain, the scale is 1:50,000. The data is updated annually, or after a major new release of DiGMap-GB. The permeability data describes the fresh water flow through these deposits and the ability of a lithostratigraphical unit to transmit water. Maximum and minimum permeability indices are given for each geological unit to indicate the range in permeability likely to be encountered and the predominant flow mechanism (fracture or intergranular). Neither of the assigned values takes into account the thickness of either the unsaturated or saturated part of the lithostratigraphical unit. The data can be used freely internally, but is licensed for commercial use. It is best displayed using a desktop GIS, and is available in vector format as ESRI shapefiles and MapInfo TAB files.