The Principal Investigator in this project was Prof Ian Woodward from University of Sheffield, with 11 co-investigators at the Centre for Ecology and Hydrology (CEH), the Forestry Commission’s Forest Research, the Agriculture and the Environment Division at Rothamsted Research, and the Universities of Aberdeen, Edinburgh, Leeds, York, Oxford and Southampton. This dataset collection contains soil model output data. QUERCC addressed land surface processes over timescales from days to centuries, with particular emphasis on the carbon cycle. Some processes are already well represented and validated in Dynamic Global Vegetation Models (DGVMs), while others that are known to impact on the carbon cycle are not. Independent carbon and vegetation data sets were compared against DVGMs to assess their current state, and further key modules were developed for nutrient cycling, which exerts a major feedback on carbon exchange, and for a greater resolution of plant processes. A global map of plant functional types that exert significant impacts on the carbon cycle was also developed.

QUERCC addresses land surface processes over timescales from days to centuries, with particular emphasis on the carbon cycle. Some processes are already well represented and validated in Dynamic Global Vegetation Models (DGVMs), while others that are known to impact on the carbon cycle are not. Independent carbon and vegetation data sets are being compared against DVGMs to assess their current state, and further key modules will be developed for nutrient cycling, which exerts a major feedback on carbon exchange, and for a greater resolution of plant processes. This dataset contains Imogen output model data

QUERCC addresses land surface processes over timescales from days to centuries, with particular emphasis on the carbon cycle. Some processes are already well represented and validated in Dynamic Global Vegetation Models (DGVMs), while others that are known to impact on the carbon cycle are not. Independent carbon and vegetation data sets are being compared against DVGMs to assess their current state, and further key modules will be developed for nutrient cycling, which exerts a major feedback on carbon exchange, and for a greater resolution of plant processes. This dataset contains a global map of plant functional types that exert significant impacts on the carbon cycle as modelled by the Rothamsted Research institute based on the FAO (Food and Agriculture Organization) soil properties.

The dataset contains measurements of fluorescein, dopachrome and nitrous oxide production from incubation experiments of streambed sediments. The sediments were collected in five pseudo-replicates from 0 to 10cm depth using a 5cm-diameter AMS slide hammer and trowel at two locations within the Wood Brook, Staffordshire, in June 2015. Samples were collected from two reaches within the stream, a mid-stream sandy reach and a downstream gravel reach. The sediment was used in laboratory incubation experiments to determine rates of fluorescein diacetate (FDA) hydrolysis (total microbial activity), extracellular phenol oxidase activity (recalcitrant carbon uptake) and potential denitrification from sand versus gravel sediments. Also included is the organic matter content of the sediments. The work was funded by the Natural Environment Research Council. Full details about this dataset can be found at https://doi.org/10.5285/500193f7-2653-4696-8224-276a734ed6ab

These data contain 408 instances of annual model output from JULES/IMOGEN simulations, covering the period between 1850-2100. Each simulation (which corresponds to one netcdf file) provides annual average of carbon stocks of the land, atmosphere and ocean store required to calculate the anthropogenic fossil fuel emissions as the residual of the yearly changes. Also included are the global warming variables, fractional land-cover, natural wetland extent and methane (CH4) flux and the soil temperature and moisture content for additional analysis. The spatial coverage is global with spatial resolution of the data is 2.5 degrees latitude, 3.75 degrees longitude. This dataset is the model output that was used in Comyn-Platt et al (2018) [ Comyn-Platt, E. et al. (2018). Carbon budgets for 1.5 and 2C targets lowered by natural wetland and permafrost feedbacks. Nature Geoscience. https://doi.org/10.1038/s41561-018-0174-9] Full details about this dataset can be found at https://doi.org/10.5285/1cebd79c-02e7-475a-a1da-1f26a963d41e

The dataset contains chemistry data from streambed porewater (10 and 20 cm) and surface water, as well as nitrogen chemistry data at 2.5 cm resolution within the upper 15 cm of the streambed. The dataset includes concentrations of dissolved organic carbon (DOC), carbon dioxide, methane, ammonium, nitrate, nitrite and nitrous oxide, and isotopic ratios of δ13CCO2, δ15NNO3+NO2 and δ18ONO3+NO2. Also included are measurements of dissolved oxygen and temperature. Samples were collected from three reaches within the stream, an upstream sandy reach, a mid-stream sandy reach and a downstream gravel reach. The work was carried out with Natural Environment Research Council (NERC) funding through a PhD (NERC award number 1602135), grant (NE/L004437/1) and Life Sciences Mass Spectrometry Facility grant (CEH_L102_05_2016). Full details about this dataset can be found at https://doi.org/10.5285/00601260-285e-4ffa-b381-340b51a7ec50

Data on the carbon and nitrogen cycling in soils from different geologies within the Hampshire Avon catchment, UK. The dataset also includes functional gene data, anion and cation concentrations, methane production and oxidation potential, and nitrification, denitrification and mineralization rates. Data were collected between February 2013 and November 2014. Data were collected to address the hypotheses of how the functional microbial community involved in carbon and nitrogen cycling changed seasonally and with geology. Data were collected as part of the project "The role of lateral exchange in modulating the seaward flux of C, N, P", funded under NERC's Macronutrients Cycles research programme. Full details about this dataset can be found at https://doi.org/10.5285/83f83414-f644-4684-ad5b-e1237fb12fc5