DOI: 10.5061/dryad.gb5mkkwm6
title: The BenBioDen database, a global database for meio-, macro- and megabenthic biomass and densities

description: 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 (&gt; 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.
description: 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 <i>Web of Science</i> 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 <i>PANGAEA® Data Publisher</i>
 (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
 <i>EOL data archive</i> (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<sup>-2</sup>, g DW m<sup>-2</sup>,
 g AFDW m<sup>-2</sup>, g or mol C m<sup>-2</sup>).
 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
 <i>Web of Science</i> 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 <i>PANGAEA® Data
 Publisher</i> (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<sup>-2</sup> or a unit that could be
 converted to ind. m<sup>-2</sup>, 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 <i>and</i> DM, we
 report the data only once (preferred units: WM &gt; DM &gt; AFDM
 &gt; 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 <i>±</i>  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.