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The biome inventory – standardizing global biogeographical land units

Citation

Fischer, Jan-Christopher; Walentowitz, Anna; Beierkuhnlein, Carl (2022), The biome inventory – standardizing global biogeographical land units, Dryad, Dataset, https://doi.org/10.5061/dryad.hqbzkh1jm

Abstract

The subdivision of the Earth's terrestrial surface into different biomes, ecozones, bio-climatic realms or other large ecological land units is an essential reference for global biogeographical and ecological studies. Various classification schemes exist. They differ significantly in terms of the considered criteria for classification and the underlying methodology of class assignments. Evident divergences between global biome concepts are elusive, weakening hereon based analyses and assumptions. Compilation and standardization are essential for obtaining a framework that enables the comparison of different products. To address this need, we created a catalogue of standardized categorial maps comprising 31 different global products based on various methodological approaches. Those were processed individually to facilitate their use in large-scale biogeographical and ecological analyses.

Methods

Spatial data of the selected classifications were retrieved from original sources depending on their availability. Certain concepts were manually digitized and geo-referenced as ESRI shapefiles based on scans of latest available map representations extracted from literature. Those classifications and others presented in vector format were transformed to grid data. A template raster file was created to serve as a reference for grid processing. All concepts were harmonized with this standard format at a spatial resolution of 10 km x 10 km, over a global extent from 180°W to 180°E and 90°N to 90°S and with the coordinate reference system set to equal-area Mollweide projection. Any undefined classes were excluded. The values of all raster cells we transformed to numbers by interchanging the names of classes that are commonly character strings with distinct values (e.g., values "1" and "2" were assigned to "Tropical rainforest" and "Savanna"). Classes were sorted according to their centre's latitudinal deviation from the equator in ascending order from 1 until the count of different classes. Inland water bodies, oceanic islands, mountains and urban areas were defined as azonal classes; thus, consistent values were assigned (inland water bodies=95, oceanic islands=96, mountains=97, urban=98). All processed classifications were combined into one RasterStack object with 31 layers in chronological order from the most recent to the oldest classification. Legends of all maps were harmonized for consistency. They are provided in an ancillary text file in the same order like the RasterStack.

Usage Notes

This data set contains a RasterStack object with 31 layers of standardized global biome and land-cover classifications (Biome_Inventory_RasterStack.tif). Legends of all maps are provided in an associated text file (Biome_Inventory_Legends.txt). They are presented in the same order like the layers in the RasterStack object.

The data set can be processed with RStudio. Exemplary code to open and visualize the RasterStack of the biome inventory from the file "Biome_Inventory_RasterStack.tif" with legend data from the file "Biome_Inventory_Legends.txt" is presented in the associated README-file (README_biome_inventory.txt).

Funding

University of Bayreuth