Assessing Patterns of Metazoans in the Global Ocean using Environmental DNA

Data for the above publication which is in RSOS. Code is available here, https://github.com/ngeraldi/Global_ocean_genome_analysis.  The 5 files include the amplicon data (Malaspina and Tara) and all metagenome data is in DMAP_biomass_apr19 (it is not biomass, it is metagenome data). Global layers contain the metadata- april18 is amplicon data and genome is the metagenome data.

Abstract:

Documenting large-scale patterns of animals in the ocean and determining the drivers of these patterns is needed for conservation efforts given the unprecedented rates of change occurring within marine ecosystems. We used existing datasets from two global expeditions, Tara Oceans and Malaspina, that circumnavigated the oceans, and sampled down to 4000 meters to assess metazoans from eDNA extracted from seawater. We describe patterns of taxonomic richness within metazoan phyla and orders based on metabarcoding and infer relative abundance of phyla using metagenome datasets, and relate these data with environmental variables. Arthropods had the greatest taxonomic richness of metazoan phyla at the surface, while cnidarians had the greatest richness in pelagic zones. Half of the marine metazoan eDNA from metagenome datasets was from arthropods, followed by cnidarians and nematodes. We found that mean surface temperature and primary productivity were positively related with metazoan taxonomic richness. Our findings concur with existing knowledge that temperature and primary productivity are important drivers of taxonomic richness for specific taxa at the ocean’s surface, but these correlations are less evident in the deep ocean. Massive sequencing of eDNA can improve understanding of animal distributions, particularly for the deep ocean where sampling is challenging.