Conversion factors for Greenland shelf benthos: Weight-to-weight and body size-to-weight relationships

File 1: Weight-to-Weight Conversion Factors Benthos.xlsx Description file 1: This dataset provides weight-to-weight conversion factors between wet mass (WM) [g], dry mass (DM) [g], and ash-free dry mass (AFDM) [g] for 43 macro- and mega-benthic families. The dataset includes taxonomic information (Phylum, Family, Genus) for each benthic taxon. The conversion factors were derived by including the WM, DM, or AFDM of all samples collected per family. For each family, the column “N” indicates the total number of individuals used. Each conversion factor of a family includes 95 % confidence intervals and squared R values (R²). Conversion factors of families with significant Spearman rank correlation tests (p-value < 0.05) are shown in bold text. These data enable reliable conversion between different biomass measures and support ecological, biogeochemical, and biodiversity studies in benthic research. File 2: Body size-to-weight Conversion factors Benthos.xlsx Description file 2: This dataset provides weight-to-body size conversion factors between wet mass (WM) [g], dry mass (DM) [g], and ash-free dry mass (AFDM) [g] and body size morphometrics (Carapax length, body diameter, disk diameter, outer diameter (across disk & arms), body length) [mm] for 43 macro- and mega-benthic families. The dataset includes taxonomic information (Phylum, Family, Genus) for each benthic taxon. The conversion factors were derived by including the WM, DM, or AFDM and body size morphometrics of all samples collected per family. For each family, the column “N” indicates the total number of individuals used. Each conversion factor of a family includes 95 % confidence intervals and squared R values (R²). Conversion factors of families with significant Spearman rank correlation tests (p-value < 0.05) are shown in bold text. These data enable reliable conversion between different biomass and body size measures and support ecological, biogeochemical, and biodiversity studies in benthic research. File 3: Weights and sizes of all benthic samples (raw data file).xlsxDescription file 3: Raw data of macro- and megabenthic samples used in the analyses. The table includes 492 samples, listing for each the sample and station number, collection coordinates (latitude and longitude), taxonomic identification (Phylum, Class, Order, Family, Genus, Species), measured morphometrics (Carapax length, body diameter, disk diameter, outer diameter (across disk & arms), body length), body size (Size) [mm], wet mass (WM) [g], dry mass (DM) [g], and ash-free dry mass (AFDM) [g].File 4: Conversion factors between biomasses (weight-to-weight).R Description & Methods file 4: This script calculates mass-conversion factors for 43 benthic invertebrate families by deriving regression slopes between the three mass types: wet mass (WM) to dry mass (DM), wet mass to ash-free dry mass (AFDM), and dry mass to ash-free dry mass. Analyses were performed in R (version 2024.04.0+735) using the functions lm() and coef() from the stats package (R Core Team, 2022).File 5: Conversion factors between body-size and biomasses (body size-to-weight).R Description & Methods file 5: This script calculates size-to-mass conversion factors for 43 benthic invertebrate families by determining regression slopes between body size (Size) and three mass types: wet mass (WM), dry mass (DM), and ash-free dry mass (AFDM). Analyses were performed in R (version 2024.04.0+735) using the functions lm() and coef() from the stats package.File 6: Levenes and Shapiro Wilk Test.R Description & Methods file 6: This script evaluates whether the variables wet mass (WM), dry mass (DM), ash-free dry mass (AFDM), and body size (Size) meet the assumptions of parametric tests by testing for homogeneity of variances and normality. Homogeneity of variances across benthic families was assessed using Levene’s test (leveneTest()) from the car package. Normality of each variable was tested using the Shapiro–Wilk test (shapiro.test()) from the stats package. To improve interpretability and explore potential transformations, variables were log-transformed (log()), square root-transformed (sqrt()), cube root-transformed (^ (1/3)), and inverse-transformed (1 / (x + 1)), while Box–Cox transformations were applied using the boxcox() function from the MASS package to identify optimal power transformations. Analyses were performed in R (version 2024.04.0+735), with all tests applied separately to each variable and its transformed versions (R Core Team, 2022). Variables failing the assumptions (Levene’s p < 0.05 for unequal variances or Shapiro–Wilk p < 0.05 for non-normality) were flagged as violating parametric assumptions, guiding the subsequent use of non-parametric analyses (Spearman rank correlations) in downstream analyses.File 7: Spearman Ranks Correlation between biomass (body weight) and body size.R Description & Methods: This script performs Spearman rank correlation tests to assess the relationships between wet mass (WM), dry mass (DM), and ash-free dry mass (AFDM). Analyses were performed in R (version 2024.04.0+735) using the function core.test() and the method spearman from the stats package (R Core Team, 2022).File 8: Spearman Ranks Correlation between body weight and body weight.R Description & Methods: This script performs Spearman rank correlation tests to assess the relationships between body size (Size) and three mass types: wet mass (WM), dry mass (DM), and ash-free dry mass (AFDM). Analyses were performed in R (version 2024.04.0+735) using the function core.test() and the method spearman from the stats package (R Core Team, 2022).