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.
Notes
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
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
genus_species: genus and species extracted from original data sources
subgroup: broad taxonomic group: finfish / crustacean / mollusc
taxon_common_name: species common name in English
location_of_study: location of sample collection
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)
lead: concentration of total lead in ug / 100g raw edible tissue.
arsenic: concentration of total arsenic in ug / 100g raw edible tissue.
cadmium: concentration of total cadmium in ug / 100g raw edible tissue.
part: body part included in the edible portion.
dataset: if the observation comes from an existing data compilation, first author of original data compilation.
bibliography: complete reference information for observation.
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).
obs_id: unique identifier for each sample in the dataset.
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
common_name: common name in English
subgroup: broad taxonomic group; mollusc, crustacean, finfish
sample_info: sample description, including information on which parts are included
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
ca_mg: concentration of calcium in edible portion, in mg / 100g edible portion (includes both elemental and ionic forms)
fe_mg: concentration of iron in edible portion, in mg / 100g edible portion (includes both elemental and ionic forms)
zn_mg: concentration of zinc in edible portion, in mg / 100g edible portion (includes both elemental and ionic forms)
epa: concentration of EPA in edible portion, in g / 100g edible portion
dha: concentration of DHA in edible portion, in g / 100g edible portion
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)
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)
location: location of sample collection
season: season of sample collection
biblio_id: unique identifier for each reference
bibliography: complete reference information for original data source
comments_on_data_processing_methods: notes describing how data were processed relative to their original source
publication_year: year of publication of original data source
food_item_id: if observation comes from an existing compilation, the id of that observation in pre-existing database
caldata: 0 or 1, corresponding to whether the sample has a calcium measurement
irondata: 0 or 1, corresponding to whether the sample has an iron measurement
zincdata: 0 or 1, corresponding to whether the sample has a zinc measurement
epadata: 0 or 1, corresponding to whether the sample has an EPA measurement
dhadata: 0 or 1, corresponding to whether the sample has a DHA measurement
proteindata: 0 or 1, corresponding to whether the sample has a protein measurement
fatdata: 0 or 1, corresponding to whether the sample has a fat measurement
data_here: total number of nutrients for which there are data for the sample
Funding provided by: Natural Sciences and Engineering Research Council of Canada
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000038
Award Number: Vanier Scholarship to JRB
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- 10.5061/dryad.rn8pk0p8t (DOI)