Premium
Associations of Community Structure and Functions of Benthic Invertebrates with Nickel Concentrations: Analyses from Field Surveys
Author(s) -
Takeshita Kazutaka M.,
Misaki Takahiro,
Hayashi Takehiko I.,
Yokomizo Hiroyuki
Publication year - 2019
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.4462
Subject(s) - benthic zone , invertebrate , biomonitoring , species richness , abundance (ecology) , environmental science , ecology , quantile , biomass (ecology) , environmental chemistry , quantile regression , biology , chemistry , mathematics , statistics
Field surveys provide valuable empirical information about the effects of heavy metals on the biological integrity of river ecosystems. To evaluate the effect of nickel (Ni) on aquatic organisms, we conducted field surveys of benthic invertebrates and Ni concentrations at 45 sites in 19 rivers in Japan. We examined the relationships between 11 structural or functional measures of benthic invertebrate communities and free Ni ion concentrations with a 90th quantile regression model. Among the measures, Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, total wet biomass of all invertebrates, and total abundance of filter feeders were negatively associated with free Ni ion concentrations. The total abundance of mud burrowers and their percentage contribution to the abundance of all invertebrates as well as the total abundances of collector‐gatherers and predators were positively associated with the Ni ion concentrations. The free ion concentrations of Ni associated with a 5% reduction of one of the 3 measures from its 90th quantile value at reference sites (EC5) were estimated to be 0.2 to 7.6 µg/L. The point estimates of EC5 were similar in order of magnitude to the environmental quality standard for Ni in the European Union. However, the usefulness of simple point estimates of effective concentrations based on quantile regression lines should be carefully examined because the uncertainties in our EC5 values were large. Environ Toxicol Chem 2019;38:1728–1737. © 2019 SETAC