The ProkaBioDen database, a global database of benthic prokaryotic biomasses and densities in the marine realm
Data files
Apr 08, 2022 version files 1.23 MB
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List_of_studies_for_ProkaBio_database.txt
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List_of_studies_for_ProkaDen_database.txt
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ProkaBio_database.xlsx
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ProkaDen_database.xlsx
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README_file.txt
Abstract
Benthic prokaryotes include Bacteria and Archaea and dominate densities of marine benthos. They play major roles in element cycles and heterotrophic, chemoautotrophic, and phototrophic carbon production. To understand how anthropogenic disturbances and climate change might affect these processes, better estimates of prokaryotic biomasses and densities are required. Hence, I developed the ProkaBioDen database, the largest open-access database of benthic prokaryotic biomasses and densities in marine surface sediments. In total, the database comprises 1,089 georeferenced benthic prokaryotic biomass and 1,875 density records extracted from 85 and 112 studies, respectively. I identified all references applying the procedures for systematic reviews and meta analyses and report prokaryotic biomasses as g C cm-3 sediment, g C g-1 sediment, and g C m-2. Density records are presented as cell cm-3 sediment, cell g-1 sediment/ sulfide/ vent precipitate, and cell m-2. This database should serve as reference to close sampling gaps in the future.
Methods
In March and June 2020, I compiled the “ProkaBio” part of the “ProkaBioDen database” applying the principles of “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA). In the so-called “Identification” step, I identified 1,553 peer-reviewed articles in the Web of Science by using the key words “microb* biomass benth*”, “benthic prokaryotic biomass”, “benth* bacteria* biomass marin*”, and “Archaea biomass marin*”. Additionally, I found 138 publications in other sources, such as PANGAEA® Data Publisher (https://www.pangaea.de/) and peer-reviewed publications known to the author. After removing duplicate publications, I screened all titles and abstracts of 1,299 studies (“Screening” step) and excluded 967 studies that did not report prokaryotic biomasses. In step 3, the so-called “Eligibility” step, I excluded in total 249 studies because they did not present prokaryotic biomasses in the marine sediment surface in standardizable units, i.e., in g C cm-3 wet sediment, g C g-1 wet sediment, g C g-1 dry sediment, or g C m-2. Furthermore, several studies lacked detailed geographical information about sampling stations or did not present primary research. Additional reasons for study exclusion were presenting prokaryotic biomasses for specific taxa instead of for all prokaryotes, being inaccessible, or introducing modelling, simulation, or experimental studies. In the final step, I included 85 studies from which I extracted 1,098 georeferenced benthic prokaryotic biomass records.
In March and June 2020, I established the “ProkaDen” part of the database that consists of records of prokaryotic density as well as of density of Bacteria and of Archaea. Following the PRISMA approach, I searched the Web of Science using the key words “marin* microb* abundance benth*”, “‘benthic bacteria’ abundance marin*”, “prokaryotic abundance marin*”, “prokaryotic density marin*”, “Archaea density abundance marin*”, “Archaea density marin*”, “Archaea abundance marin* benth*”, “Crenarchaea density abundance marin*”, “Crenarchaea density marin*”, “Crenarchaea abundance marin* benth*”, “Euryarchaea density abundance marin*”, and “Euryarchaea abundance marin* benth*” and found 1,204 peer-reviewed articles. I was aware of 171 additional studies that I included in the dataset which contained 1,104 studies after removing duplicates. In step 2 of the PRISMA approach (“Screening” step), I excluded 752 studies because they did not report benthic prokaryotic densities. In the “Eligibility” step, I furthermore omitted 239 studies because they did not present surface sediment prokaryotic densities or densities of a reduced number of prokaryotic taxa instead of reporting densities of all prokaryotes. I also removed studies that showed prokaryotic densities in poor-quality figures impeding data extraction and studies that listed densities which could not be converted to the common density units cell cm-3 dry sediment, cell cm-3 wet sediment, cell g-1 dry sediment, cell g-1 dry sulfide, cell g-1 vent precipitate, cell g-1 wet sediment, or cell m-2. I also excluded studies that reported experimental or culture studies and publications that I could not access. In the last step, I included 112 studies in the global benthic prokaryotic density database from which I extracted 1,875 georeferenced benthic prokaryotic density records.