Predicting sport fish mercury contamination in heavily managed reservoirs: Implications for human and ecological health.

ABSTRACT: Mercury (Hg) is a concerning contaminant due to its widespread distribution and tendency to accumulate to harmful concentrations in biota. We used a machine learning approach called random forest (RF) to test for different predictors of Hg concentrations in three species of Colorado reservoir sport fish. The RF approach indicated that the best predictors of 864 mm northern pike (Esox lucius) Hg concentrations were covariates related to salmonid stocking in each study system, while system-specific metrics related to productivity and forage base were the best predictors of Hg concentrations of 381 mm smallmouth bass (Micropterus dolomieu), and walleye (Sander vitreus). Protecting human and ecological health from Hg contamination requires an understanding of fish Hg concentrations and variabi

SUBMITTER: Lepak JM 

PROVIDER: S-EPMC10443864 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature