%0 Journal Article %A Giovanni Caudullo %T Applying geospatial semantic-array programming for a reproducible set of bioclimatic indices in Europe %D 2014 %R 10.1101/009589 %J bioRxiv %P 009589 %X Bioclimate-driven regression analysis is a widely used approach for modelling ecological niches and zonation. Although the bioclimatic complexity of the European continent is high, a particular combination of twelve climatic and topographic covariates was recently found able to reliably reproduce the FAO ecological zoning for forest resources assessment at pan-European scale, generating the first fuzzy similarity map of FAO ecozones in Europe. The reproducible procedure followed to derive this collection of bioclimatic indices is now presented. It required an integration of data-transformation modules (D-TM) using both geospatial tools such as GIS software, and array-based mathematical implementation such as semantic array programming (SemAP). Base variables, intermediate and final covariates are described and semantically defined by providing the workflow of D-TMs and the mathematical formulation following the SemAP notation. Source layers to derive base variables were extracted by exclusively relying on global-scale public open geodata in order for the same set of bioclimatic covariates to be reproducible in any region worldwide. In particular, two freely available datasets were exploited for temperature and precipitation (WorldClim) and elevation (Global Multi-resolution Terrain Elevation Data). The working extent covers the whole European continent to the Urals with a resolution of 30 arc-second. The proposed set of bioclimatic covariates will be made available as open data in the European Forest Data Centre (EFDAC). The forthcoming complete set of D-TM codelets will enable the twelve covariates to be easily reproduced and expanded through free software. %U https://www.biorxiv.org/content/biorxiv/early/2014/09/25/009589.full.pdf