Meiofauna abundance and distribution predicted with random forest regression in the German exploration area for polymetallic nodule mining, Clarion Clipperton Fracture Zone, Pacific

The dataset contains counts of meiofauna organisms on high taxonomic level and predicted distributions computed for overall meiofauna abundance, diversity (Simpson's Index D and Evenness E), richness (ntax) and individual taxa using random forest regressions. Furthermore, a habitatmap is provided, dividing the area based on k-means clustering of combined predicted distributions, bathymetry and backscatter. The spatial layers are saved as grid-files, being the standard format of the R-package \"raster\" (https://cran.r-project.org/web/packages/raster/index.html). […]