Global ensembles of Ecosystem Service map outputs modelled at 1km resolution for water supply, recreation, carbon storage, fuelwood and forage production

The ensembles, their approach methodology, and their validations are currently in revision after review in Science Advances as Willcock et al. (2023): Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps. Relevant Matlab and Python codes can be found at https://github.com/GlobalEnsembles

Global among model ensembles for recreation, carbon storage, and biomass for fuelwood and forage production are provided as 1-km2 gridcells; water supply ensembles are provided per catchment polygons associated to the 15,289 worldwide HydroSHEDS catchment definitions (https://www.hydrosheds.org/). Model data included outputs from among others: InVEST, ARIES, WaterWorld, Co$ting Nature, LPJ-GUESS, TEEB, Scholes, Aqueduct, FAO livestock distributions, and a wide variety of biomass models such as from ESA CCI Biomass Climate Change Initiative, GEOCARBON global forest biomass and Global Forest Watch. 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 and weighted averaging with weights determined following multiple methods according to Hooftman et al. (2022): the deterministic correlation coefficient among models, the first principal component among models and weights iterated as regression to the median and leave-one-out cross validation. 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.

Related datasets

Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods

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