DOI: 10.5061/dryad.rn8pk0p8t
title: Aquatic biodiversity enhances multiple nutritional benefits to humans

description: Humanity depends on biodiversity for health, well-being and a stable
 environment. As biodiversity change accelerates, we are still discovering
 the full range of consequences for human health and well-being. Here, we
 test the hypothesis -- derived from biodiversity - ecosystem functioning
 theory -- that species richness and ecological functional diversity allow
 seafood diets to fulfill multiple nutritional requirements, a condition
 necessary for human health. We analyzed a newly synthesized dataset of
 7245 observations of nutrient and contaminant concentrations in 801
 aquatic animal taxa, and found that species with different ecological
 traits have distinct and complementary micronutrient profiles, but little
 difference in protein content. The same complementarity mechanisms that
 generate positive biodiversity effects on ecosystem functioning in
 terrestrial ecosystems also operate in seafood assemblages, allowing more
 diverse diets to yield increased nutritional benefits independent of total
 biomass consumed. Notably, nutritional metrics that capture multiple
 micronutrients essential for human well-being depend more strongly on
 biodiversity than common ecological measures of function such as
 productivity, typically reported for grasslands and forests. Further, we
 found that increasing species richness did not increase the amount of
 protein in seafood diets, and also increased concentrations of toxic metal
 contaminants in the diet. Seafood-derived micronutrients are important for
 human health and are a pillar of global food and nutrition security. By
 drawing upon biodiversity-ecosystem functioning theory, we demonstrate
 that ecological concepts of biodiversity can deepen our understanding of
 nature’s benefits to people and unite sustainability goals for
 biodiversity and human well-being.
description: Data were collected by extracting data from previously published
 articles. Please see Bernhardt and O'Connor 2021, PNAS for detailed
 Methods.
description: Metadata for Bernhardt and O'Connor 2021 - North American
 seafood contaminant dataset
 ("seafood-contaminant-data-cleaned.csv")
 obs_id: unique identifier for each contaminant
 observation<br> taxon_name: genus and species, checked against one
 of the following taxonomic data sources: Catalogue of Life, Encyclopedia
 of Life, GBIF Backbone Taxonomy, World Register of Marine Species,
 OBIS<br> genus_species: genus and species extracted from original
 data sources<br> subgroup: broad taxonomic group: finfish /
 crustacean / mollusc<br> taxon_common_name: species common name in
 English<br> location_of_study: location of sample
 collection<br> methylmercury: concentration of methylmercury in ug /
 100g raw edible tissue. Methylmercury was calculated from total mercury
 following Sunderland et al. 2007 (assuming methylmercury  = 95% of total
 mercury in finfish and crustaceans, 30% of total mercury in
 molluscs)<br> lead: concentration of total lead in ug / 100g raw
 edible tissue.<br> arsenic: concentration of total arsenic in ug /
 100g raw edible tissue.<br> cadmium: concentration of total cadmium
 in ug / 100g raw edible tissue.<br> part: body part included in the
 edible portion.<br> dataset: if the observation comes from an
 existing data compilation, first author of original data
 compilation.<br> bibliography: complete reference information for
 observation.<br> number_of_samples: if applicable, the number of
 individuals or individual samples included in contaminant concentration
 estimation. Metadata for Bernhardt and O'Connor
 2021 - Global seafood nutrient dataset
 ("global-seafood-nutrient-dataset-raw.csv")
 All nutrient concentrations are presented per 100 g edible
 portion on a fresh weight basis, for only raw or frozen samples (no
 prepared seafood items).<br> obs_id: unique identifier for each
 sample in the dataset. <br> taxon_name: scientific name (genus and
 species), as resolved with one of the following taxonomic data sources:
 Catalogue of Life, Encyclopedia of Life, GBIF Backbone Taxonomy, World
 Register of Marine Species, OBIS<br> common_name: common name in
 English<br> subgroup: broad taxonomic group; mollusc, crustacean,
 finfish<br> sample_info: sample description, including information
 on which parts are included<br> body_part: for finfish samples, body
 part in the edible portion sample; muscle (fillet or skinless fillet),
 muscle and organs (including bones, liver, etc), eggs, liver,
 oil<br> ca_mg: concentration of calcium in edible portion, in mg /
 100g edible portion (includes both elemental and ionic forms)<br>
 fe_mg: concentration of iron in edible portion, in mg / 100g edible
 portion (includes both elemental and ionic forms)<br> zn_mg:
 concentration of zinc in edible portion, in mg / 100g edible portion
 (includes both elemental and ionic forms)<br> epa: concentration of
 EPA in edible portion, in g / 100g edible portion<br> dha:
 concentration of DHA in edible portion, in g / 100g edible
 portion<br> fat: concentration of fat in edible portion, in g / 100g
 edible portion (total fat; following INFOODS, calculated as one of the
 following: sum of triglycerides, phospholipids, sterols and related
 compounds; derived by analysis using continuous extraction, method of
 determination unknown or mixed methods)<br> protein: concentration
 of protein in edible portion, in g / 100g edible portion (total protein;
 following INFOODS, calculated by any of the following methods: calculated
 from total nitrogen, calculated from protein nitrogen, method of
 determination unknown or variable)<br> location: location of sample
 collection<br> season: season of sample collection<br>
 biblio_id: unique identifier for each reference<br> bibliography:
 complete reference information for original data source<br>
 comments_on_data_processing_methods: notes describing how data were
 processed relative to their original source<br> publication_year:
 year of publication of original data source<br> food_item_id: if
 observation comes from an existing compilation, the id of that observation
 in pre-existing database<br> caldata: 0 or 1, corresponding to
 whether the sample has a calcium measurement<br> irondata: 0 or 1,
 corresponding to whether the sample has an iron measurement<br>
 zincdata: 0 or 1, corresponding to whether the sample has a zinc
 measurement<br> epadata: 0 or 1, corresponding to whether the sample
 has an EPA measurement<br> dhadata: 0 or 1, corresponding to whether
 the sample has a DHA measurement<br> proteindata: 0 or 1,
 corresponding to whether the sample has a protein measurement<br>
 fatdata: 0 or 1, corresponding to whether the sample has a fat
 measurement<br> data_here: total number of nutrients for which there
 are data for the sample