Data of 'Towards an ecosystem service-based method to quantify the filtration services of mussels under chemical exposure'

DOI

In our paper ‘Towards an ecosystem service-based method to quantify the filtration services of mussels under chemical exposure’ (https://doi.org/10.1016/j.scitotenv.2020.144196), we derived a methodology for quantifying the economic benefits of mussel filtration services in relation to chemical mixture exposure. To this end, we first applied the bootstrapping approach to quantify the filtration capacity of dreissenid mussels when exposed to metal mixtures in the Rhine and Meuse Rivers in the Netherlands. Subsequently, we applied the value transfer method to quantify the economic benefits of mussel filtration services to surface water-dependent drinking water companies. We estimated that dreissenid filtration services would save 110–12,000 euros/million m3 for drinking water production when abstracting raw water at the end of respective rivers. This study presents a novel methodology for quantifying the economic benefits of mussel filtration services associated with chemical pollution, which is understandable to policymakers. The derived approach could potentially serve as a blueprint for developing methods in examining the economic value of other filter-feeders exposed to other chemicals and environmental stressors.This dataset contains data on surface area and length of groynes for the Rhine and Meuse River in the Netherlands and metal exposure effects on dreissenid behaviours (filtration rate and valve closure). Data on surface area and length of groynes were retrieved from ecotope maps from Rijkswaterstaat (http://www.rijkswaterstaat.nl/). Data on metal exposure effects on dreissenid behaviours were obtained from the United States Environmental Protection Agency ECOTOX database.

Identifier
DOI https://doi.org/10.17026/dans-29f-vzcn
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-29f-vzcn
Provenance
Creator J. Wang; K. Remon Koopman; F.P.L. Collas; L. Posthuma; TON de Nijs; R.S.E.W. Leuven; A.J. Hendriks
Publisher DANS Data Station Life Sciences
Contributor RU Radboud University
Publication Year 2022
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format text/xml; application/pdf; text/plain; application/zip; text/csv
Size 6827; 118775; 938; 22706; 11504; 38987; 102588
Version 1.0
Discipline Earth and Environmental Science; Environmental Research; Geosciences; Natural Sciences