a9ae773d-b742-4d42-ae42-2b594bae5d38
English
ISO/IEC 8859-1 (also known as Latin 1)
dataset
dataset
NERC EDS Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg
Lancaster
LA1 4AP
UK
info@eidc.ac.uk
https://eidc.ac.uk/
EIDC website
The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences.
information
pointOfContact
2024-02-27T16:22:11
UK GEMINI
2.3
OSGB 1936 / British National Grid
Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods
2021-11-22
publication
https://catalogue.ceh.ac.uk/id/a9ae773d-b742-4d42-ae42-2b594bae5d38
10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38
doi:
Hooftman, D.A.P., Bullock, J.M., Jones, L., Willcock, S. (2021). Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods. NERC EDS Environmental Information Data Centre 10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38
This data set contains UK-wide maps of ten different among-model ensemble approaches for two services: above ground Carbon stock and water supply. The data for Carbon comes as fourteen TIF maps for above ground carbon storage at a 1-km2 resolution with associated world files: ten approaches, with a double option for two of those, together with maps of variation among models and among ensembles. For water, the data comes as one shapefile with polygons per watershed, each polygon containing these fourteen estimates. For all maps, 600dpi jpg depictions are added to the supporting information. Directory location independent layer files are included to aid scaling and providing the colour palettes. Ensemble output maps were calculated with different approaches following the supporting documentation and associated publication. Uncertainty estimates for these services are included as variation among contributing model outputs and among the employed ensemble approaches. 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/a9ae773d-b742-4d42-ae42-2b594bae5d38
Hooftman, D.A.P.
Lactuca: environmental data analyses and Modelling
enquiries@ceh.ac.uk
https://orcid.org/0000-0001-9835-6897
ORCID record
ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers.
information
author
Bullock, J.M.
UK Centre for Ecology & Hydrology
enquiries@ceh.ac.uk
https://orcid.org/0000-0003-0529-4020
ORCID record
ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers.
information
author
Jones, L.
UK Centre for Ecology & Hydrology
enquiries@ceh.ac.uk
https://orcid.org/0000-0002-4379-9006
ORCID record
ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers.
information
author
Willcock, S.
Bangor University
enquiries@ceh.ac.uk
https://orcid.org/0000-0001-6704-3548
ORCID record
ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers.
information
author
Hooftman, D.A.P.
Lactuca: environmental data analyses and Modelling
enquiries@ceh.ac.uk
pointOfContact
NERC EDS Environmental Information Data Centre
enquiries@ceh.ac.uk
custodian
NERC EDS Environmental Information Data Centre
enquiries@ceh.ac.uk
publisher
Bangor University
enquiries@ceh.ac.uk
owner
Land Cover
Hydrography
theme
GEMET - INSPIRE themes, version 1.0
2008-06-01
publication
otherRestrictions
no limitations
otherRestrictions
This resource is available under the terms of the Open Government Licence
otherRestrictions
If you reuse this data, you should cite: Hooftman, D.A.P., Bullock, J.M., Jones, L., Willcock, S. (2021). Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38
grid
25
10
5
20
46000
1000
10000
English
utf8
inlandWaters
biota
-8.648
1.768
49.864
60.861
TIFF
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
distributor
https://catalogue.ceh.ac.uk/datastore/eidchub/a9ae773d-b742-4d42-ae42-2b594bae5d38
Download the data
Download a copy of this data
download
https://data-package.ceh.ac.uk/sd/a9ae773d-b742-4d42-ae42-2b594bae5d38.zip
Supporting information
Supporting information available to assist in re-use of this dataset
information
dataset
dataset
Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
2010-12-08
The ensembles, their approach methodology, and their validations are currently under review in Ecosystem Services as Hooftman et al. (2022): Weighted Ensembles Reduce Uncertainty in Ecosystem Service Modelling. Relevant Matlab and Python codes can be found at github.com/EnsemblesTypes. Among model ensembles for above ground standing carbon are provided as 1-km2 gridcells; Water supply ensembles are provided per catchment polygons associated to the 519 selected National River Flow Archive gauging stations in this study. Model data included outputs from among others: InVest, ARIES, WaterWorld, LUCI, LPJ-GUESS, TEEB, Scholes, Aqueduct, Grid-to-Grid, and DECIPHeR. These data sets are not provided here, but a full list with links to these data sets or software, where applicable, can be found in the supporting documentation. Note that license restrictions could apply. Ensembles approaches include: unweighted (mean and median) approaches, weighted averaging with weights determined following multiple methods (deterministic and iterative), attribute weighted averaging, and trained approaches. Uncertainty is presented by the Standard Error of Mean among contributing model outputs and among ensemble approaches, calculated as the standard deviation corrected with the amount of contributing models/ensembles per cell. Prior to ensemble calculations: all individual model outputs have been normalised against the lower 2.5% and upper 97.5% percentile. Afterwards, the resulting Ensembles have been identically re-normalised to ensure a 0-1 scale. For all details about the individual model approaches, their synchronisation, ensemble algorithms and their validation we refer to the supporting documentation and associated publication.