Weight-to-weight conversion factors for benthic macrofauna: recent measurements from the Baltic and the North Seas

. Estimates of biomass often involve the use of weight-to-weight conversion factors for rapid assessment of dry-weights based metrics from more widely available measurements of wet weights. Availability of standardized biomass data is essential amid research onfor studying population dynamics, energy flow, fisheryflows, fisheries and food web interactions. To make the estimates of biomass consistent weight-to-weight conversion factors are often used, for example to translate more 10 widely available measurements of wet-weights into required dry-weights and ash-free dry-weights metrics. However, for many species and groups the widely-applicable freely available conversion factors until now remained very rough approximations with high degree of taxonomic generalization. To close up this gap, here for the first time we publish the most detailed and statically robust list of ratios of wet -weight (WW), dry -weight (DW) and ash-free dry -weight (AFDW). The dataset includes over 1700017.000 records of single measurements for 497 taxa. Along with aggregated calculations, enclosed reference 15 information with sampling dates and geographical coordinates the dataset provides thea broad opportunity for reuse and repurposing. It empowers the future user to do targeted sub selections of data to best combine them with own local data, instead of only having a single value of conversion factor per region. DataThe dataset can helpthereby be used to quantify natural variability and uncertainty, and assist to refine current ecological theory. The dataset is available via an unrestricted repository from: http://doi.io-warnemuende.de/10.12754/data-2021-0002-01 (Gogina et al., 2021).

biodiversity in the second half of the last century, primarily efforts from the Baltic Sea pioneered publishing thein publication of compilations of conversion factors for marine macroinvertebrates (Thorson, 1957;Lappalainen and Kangas, 1975;Rumohr 30 et al., 1987), that later expanded to other geographic regions (Petersen and Curtis, 1980;Tumbiolo and Downing, 1994;Ricciardi and Bourget, 1998;Brey et al., 2010). However, though allowallowing general biomass estimates, for many species and groups, the available widely-applicable conversion factors for data standardization remain very rough approximations of weight-to-weight relationships. For example, the global database for meio-, macro-and megabenthic biomass and densities that was recently published by Stratmann et al. (2020) includes only a little share of measured ash-free dry -weights and cites 35 only a handful of publications (including those listed above) that provide such broadly used sets of values for the corresponding conversion. This highlights the importance of presentedthe present compilation.
Here for the first time we publish the taxonomically most detailed and statically most robust list of ratios of wet -weight (WW), dry -weight (DW) and ash-free dry -weight (AFDW) based on over 17.000 measurements for 497 taxa from the Baltic and the North Seas (ZettlerGogina et al., 2021). All well curated raw and aggregated data is currently stored in the open access 40 repository together with the basic usage information. Here in theIn this data descriptordescription paper we describe methods and algorithms used and provide details on metadata, structure and content of the dataset.
Our dataset can assist the studies where information on biomass has thea central role by helping to more accurately translate WW into the more relevant AFDW. Data presented here are of use for a range of scientific studies, including: (i) facilitating spatial and temporal comparison of secondary production and energy flow in marine ecosystems 45 (ii) assessment of species contribution to ecosystem functioning; supporting the generation of empirical models and predictive mapping of ecosystem services provided by marine benthic macroinvertebrates, by ensuring the most use of best taxonomic resolution and information on biomass (iii) enabling user-defined sub-selection of data, that can be combined with own local data, instead of relying on single average number per large region 50 2 Materials and methods Macrobenthic specimens were collected over the period from 1986 to 2020 in the Baltic and the North Sea ( Fig. 1 and Table   1). Following HELOCM guidelines on sampling soft bottom macrofauna (HELCOM, 2017) most samples that were used for measurements included in the dataset were collected using Van Veen grab or 1-m dredge (type Kieler Kinderwagen). From hard-bottom habitats samples where partly derived by divers (Beisiegel et al., 2017). Routinely, samples were stored for at 55 least three months before weighing. Biomass determination was carried out separately for each taxon. All nesting species like polychaetes or hermit crabs were removed from tubes or shells. Molgula manhattensis, a species ofan ascidian species, and phoronids (represented solely by Phoronis sp.) require a special remark. As a rule, both taxa can hardly be separated from the glued grains of sand, which is why an exception has been made here. With these organisms the grains of sand were also commonly weighed in the laboratory routine. However, as desired, the AFDW only specifies the organic content, since sand and ash were deducted from that weight. Biomass of molluscs and echinoderms was measured with shells. The database only includes values based on individuals with wet -weight exceeding 0.5 mg. The dry -weight was estimated after drying the formalin material at 60°C to constant weight (for 12-24 hours, or longer, depending on material thickness). After determination of dry -weight, ash-free dry -weight was measured following incineration at 500°C in a muffle furnace until weight constancy was reached. AFDW is recommended as the most accurate measure of biomass (Rumohr et al., 1987). Species nomenclature 65 has been standardised in line with the World Register of Marine Species (WoRMS Editorial Board, 2021). In the continuous complementation of theThe database is continuously enlarged, with main efforts were targeted to obtain sufficient number of measurements for reliable estimates and to cover as many frequent and characteristic species per region as possible ( Table 2).
The groups used in the dataset in order to facilitate the summary should be rather considered as functional, i.e. not strictly taxonomic, as they vary in rank ranging from Phylum to Order level. A word of caution should also be given regarding mean 70 and confidence interval values reported in Table 2 3 Data availability and usage note All measurements are available from IOW data repository: http://doi.io-warnemuende.de/10.12754/data-2021-0002-01 (Gogina et al., 2021). We have included all quality-assured measurements values without prejudice. Reporting errors and updates of the data will be done periodically issued. Users are encouraged to use the latest version of the data set according to the 'Related' note publishedlisted (under the 'versions' tab) at IOW repository. This contribution is based on data release 12.0. 80 There are no limitations on the use of these data.
Author contributions. MG aided in data collection, adapted the dataset and prepared the paper with contributions from all coauthors. AZ compiled and maintained the database and managed the quality assurance. MLZ secured funding, determined sampling strategies, conceived the investigation and ran the data collection campaigns. 85 Competing interests. The authors declare that they have no conflict of interest. Rumohr, H., Brey, T. and Ankar, S.: A compilation of biometric conversion factors for benthic invertebrates of the Baltic Sea.

130
Colour of symbols indicate habitats of the Baltic Sea (in red) and the North Sea (in blue). Data points may represent multiple observations at that locality. Projection: ETRS89 Lambert Azimuthal Equal-Area. Table 2: Weight-to-weight conversion factors for 29 major functional groups, differentiated by region, based on all raw values per taxa included in the group: AFDW = ash-free dry -weight, WW = wet -weight. DW = whole dry -weight, CI = 95% confidence interval, N = number of values, SPP = number of species (taxa) per group.