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The BenBioDen database, a global database for meio-, macro- and megabenthic biomass and densities

Cite this dataset

Stratmann, Tanja et al. (2021). The BenBioDen database, a global database for meio-, macro- and megabenthic biomass and densities [Dataset]. Dryad. https://doi.org/10.5061/dryad.gb5mkkwm6

Abstract

Benthic fauna refers to all fauna that live in or on the seafloor, which researchers typically divide into size classes meiobenthos (32/ 64 µm – 0.5/ 1 mm), macrobenthos (250  µm – 1 cm), and megabenthos (> 1 cm). Benthic fauna play important roles in bioturbation activity, mineralization of organic matter, and in marine food webs. Evaluating their role in these ecosystem functions requires knowledge of their global distribution and biomass. We therefore established the BenBioDen database, the largest open-access database for marine benthic biomass and density data compiled so far. In total, it includes 11,792 georeferenced benthic biomass and 51,559 benthic density records from 384 and 600 studies, respectively. We selected all references following the procedure for systematic reviews and meta-analyses, and report biomass records as grams of wet mass, dry mass, or ash-free dry mass, or carbon per m2 and as abundance records as individuals per m2. This database provides a point of reference for future studies on the distribution and biomass of benthic fauna.

Methods

In April and May 2019, we compiled the “BenBio” part of the “BenBioDen database” following the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) Statement for systematic reviews and meta-analyses. In the first PRISMA step, the “Identification” step, we identified 1,373 articles in the Web of Science using the key words “marine meiofauna biomass”, “marine macrofauna biomass”, “marine megafauna biomass”, “marine meiobenth* biomass”, “marine macrobenth* biomass”, “marine megabenth* biomass”, “nematode biomass”, and “benthic ‘standing stock’”. We located an additional 201 publications based on expert knowledge. A search of the PANGAEA® Data Publisher (https://www.pangaea.de/) identified 1,488 datasets representing 148 publications using the key words “meiofauna biomass”, “macrofauna biomass” and “megafauna biomass”. Further 30 datasets were found in the EOL data archive (http://data.eol.ucar.edu/), through citations in review papers, and based on expert knowledge. After removing duplicates, we screened the titles and abstracts of 1,445 studies in PRISMA step 2 (“Screening”; Fig. 1A). This step excluded 951 studies because they did not report biomass values. In the Eligibility step, we assessed full texts of 494 studies for eligibility and excluded 110 studies because they did not report biomass, the publications or data were not accessible, or they did not report benthic biomass in appropriate units (g WW m-2, g DW m-2, g AFDW m-2, g or mol C m-2). Further reasons for excluding full texts included combining benthic biomass for several size classes, reporting benthic biomass for particular taxa rather than the whole size class, presenting biomass for faunal assemblages and/ or a group of sampling stations rather than for individual stations, not presenting primary research or lacking geographical details about sampling stations. We also excluded studies that estimated benthic biomass using modelling approaches, that conducted manipulative experiments, or did not report benthic biomass as single values, means or median values, but instead as ranges. The final “BenBio” part included 384 studies from which we extracted 11,792 georeferenced benthic biomass entries.

 

The Benthos Density, i.e. “BenDen”, part of the “BenBioDen” database was established in July and August 2019 following the PRISMA Statement for systematic reviews and meta-analyses. In the Identification step, we found 2,515 articles in the Web of Science using the key words “meiofauna abundance”, “meiobenthos abundance”, “macrofauna abundance”, “macrobenthos abundance”, “megafauna abundance”, “megabenthos abundance”, “meiofauna Arctic Ocean”, “meiofauna Atlantic Ocean”, “meiofauna Black Sea”, “meiofauna Gulf of Mexico”, “meiofauna Indian Ocean”, “meiofauna Mediterranean Sea”, “meiofauna Pacific Ocean”, “meiofauna Southern Ocean”, “meiofauna Red Sea”, “meiofauna Pacific Ocean”, “megafauna Southern Ocean”, “megafauna Red Sea”, “megafauna Pacific Ocean”, “megafauna Mediterranean Sea”, “megafauna Indian Ocean”, “megafauna Black Sea”, “megafauna Gulf of Mexico”, “megafauna Atlantic Ocean”, “megafauna Arctic Ocean”, “macrofauna Arctic Ocean”, “macrofauna Atlantic Ocean”, “macrofauna Black Sea”, “macrofauna Southern Ocean”, “macrofauna Red Sea”, “macrofauna Pacific Ocean”, “macrofauna Gulf of Mexico”, “macrofauna Indian Ocean”, and “macrofauna Mediterranean Sea”. Expert knowledge identified a further 232 publications. Consulting PANGAEA® Data Publisher (https://www.pangaea.de/) identified 1,549 datasets from 172 publications using the key words “meiofauna abundance”, “macrofauna abundance” and “megafauna abundance”. Expert knowledge or unpublished datasets added a further 21 datasets. After removal of duplicates, the “Screening” step filtered 2,086 titles and abstracts and excluded 1,133 studies because they did not report benthic densities. The third PRISMA step assessed 953 studies and excluded 353 studies because they did not report metazoan meiobenthic, macrobenthic, or invertebrate megabenthic densities or they combined multiple size classes or sampling stations. We excluded other studies in the database that reported experimental studies, were inaccessible, or reported densities in a unit other than ind. m-2 or a unit that could be converted to ind. m-2, or reported densities for specific taxa instead of the entire size class. Studies were also excluded when they reported meta-studies or reviews rather than primary research, presented results of models, lacked sufficient geographical detail about sampling locations, or reported fauna associated with whale falls. The final “BenDen” part consisted of 600 studies from which we extracted 51,559 georeferenced benthic density records.

 

For 12% (BioBen part) and 4% (BioDen part) of all data records, no exact sampling location in geographical coordinates (latitude, longitude) was indicated. For these cases, we approximated the coordinates of the sampling locations using Google Maps based on information about sampling area or based on maps presented in the original publications. We labelled these data records as ‘approximated location’.

For studies that presented biomasses in several units, such as WM and DM, we report the data only once (preferred units: WM > DM > AFDM > C). The authors of this study intended to report all data records in the ‘raw’ units in which benthic fauna was measured initially. Whenever unknown conversion factors precluded calculating biomass back to ‘raw’ units, we noted this issue in the database using the label ‘converted data’ and listed references for the individual biomass conversion factors in the database.

The authors of the various studies compiled in this database sometimes used different lower and upper limits (in mm) for mesh sizes of nets and/ or sieves to define the size class. Whenever an original study reported a lower and/ or upper limit mesh size, we included this information in the database as ‘sieve mesh size (mm) lower limit’ and ‘sieve mesh size (mm) upper limit’. Studies lacking this information were scored as NA.

For those studies that reported data as mean or median ±  error terms, we incorporated only mean or median values into the database. In all cases that did not report benthic biomasses and/ or densities in the text or in tables, but presented them in figures, we extracted biomass and/ or density values from these figures using ImageJ.

Funding

European Union EMODnet Thematic Lot n° 5 – BIOLOGY*, Award: EASME/EMFF/2016/1.3.1.2- Lot 5/SI2.750022

European Commission, Award: 678760

Dutch Research Council, Award: 856.18.003

Dutch Research Council, Award: 864.13.007

Dutch Research Council, Award: 019.182EN.012

European Union EMODnet Thematic Lot n° 5 – BIOLOGY, Award: EASME/EMFF/2016/1.3.1.2- Lot 5/SI2.750022