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Uhlenkott, Katja; Vink, Annemiek; Kuhn, Thomas; Martínez Arbizu, Pedro (2020): Meiofauna abundance and distribution predicted with random forest regression in the German exploration area for polymetallic nodule mining, Clarion Clipperton Fracture Zone, Pacific. PANGAEA,

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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" (
Study area is an area allocated to the German Federal Institute for Geosciences and Natural Resources for the exploration of polymetallic nodule mining. Deep-sea mining highly endangers the benthic communities; hence the definition of preservation zones, not only for preservation but also to enable the re-settlement of mined areas, is highly important. These datasets on the spatial distribution of meiofauna have been used to account for a modelling approach to find areas with similar environmental conditions and similar benthic communities.
distribution model; Habitat Mapping; meiofauna; random forest regression
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Uhlenkott, Katja; Vink, Annemiek; Kuhn, Thomas; Martínez Arbizu, Pedro (2020): Predicting meiofauna abundance to define preservation and impact zones in a deep-sea mining context using random forest modelling. Journal of Applied Ecology,
Median Latitude: 11.887791 * Median Longitude: -117.620605 * South-bound Latitude: 11.194750 * West-bound Longitude: -119.307217 * North-bound Latitude: 13.187250 * East-bound Longitude: -116.162650
Date/Time Start: 2010-04-26T00:00:00 * Date/Time End: 2016-05-11T00:00:00
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