Lactuca: Environmental Data Analyses and Modelling
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This dataset contains the gridded estimates per 1 km2 for mean and median ensemble outputs from 4-6 individual ecosystem service models for Sub-Saharan Africa, for above ground Carbon stock, firewood use, charcoal use and grazing use. Water use and supply are identically supplied as polygons. Individual model outputs are taken from previously published research. Making ensembles results in a smoothing effect whereby the individual model uncertainties are cancelled out and a signal of interest is more likely to emerge. Included ecosystem service models were: InVEST, Co$ting Nature, WaterWorld, Monetary value benefits transfer, LPJ-GUESS and Scholes models. Ensemble outputs have been normalised, therefore these ensembles project relative levels of service across the full area and can be used, for example, for optimisation or assignment of most important or sensitive areas. The work was completed under the "EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models" project (NE/T00391X/1) funded by the UKRI Landscape Decisions programme. Full details about this dataset can be found at https://doi.org/10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f
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[This dataset is embargoed until December 15, 2025]. Data comprise of 13 different ecosystem services that were modelled at the 1 km2 resolution across Great Britain, mostly using data from 2015. The ecosystem services modelled were potential crop Production (in terms of calories), pollinator visits, greenhouse gas sequestration, two measures of biodiversity (biodiversity conservation index and richness index), erosion avoided, potential grassland productivity, nutrient retention, water retention, water yield, and potential timber yield. Full details about this dataset can be found at https://doi.org/10.5285/ea7f988d-5efe-44f9-84e9-2e4006166cf6
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This dataset contains recreation demand maps for the UK based on weekly, monthly and yearly visit frequencies. Recreation includes activities such as walking, hiking, cycling, etc, i.e., ‘outdoor non-vehicular recreation’. Recreation demand was calculated as the number of projected visits for local recreation, estimated using the universal law of human mobility (Schläpfer et al., 2021, Nature). Recreation demand maps are supplied at 250 m resolution in a British National Grid transverse Mercator projection (EPSG 27700). For each visit frequency (weekly, monthly and yearly), there is a map with and without attractiveness included in the calculation, where protected areas are used a proxy for attractiveness. This research was funded by the Natural Environment Research Council (NERC) under research programme NE/W005050/1 AgZero+ : Towards sustainable, climate-neutral farming. AgZero+ is an initiative jointly supported by NERC and the Biotechnology and Biological Sciences Research Council (BBSRC). Full details about this dataset can be found at https://doi.org/10.5285/bd3bf607-a3b2-423b-b07b-9c41e84746ee