Mixed Model Approaches Can Leverage Database Information to Improve the Estimation of Size-Adjusted Contaminant Concentrations in Fish Populations
Abstract
Concentrations of bioaccumulative contaminants in fish increase with their size and age; thus, research and monitoring of these contaminants in fish across space and time can be confounded by size covariation. To account for this, size-standardization of contaminant concentrations within fish samples is a common practice. Standardized concentrations are often estimated using within-sample regression models, also known as power series regression (referred to here as sampling event regressions, or SERs). This approach requires higher sample sizes than mixed effect models (MEMs), which are suited for this application but are not as commonly used. Herein we compare SERs to three MEM approaches; restricted maximum likelihood, Bayesian inference via Markov chain Monte Carlo (MCMC), and approximate Bayesian inference with nested Laplace approximation (INLA). We did this for two contaminants …
abstract: “Concentrations of bioaccumulative contaminants in fish increase with their size and age; thus, research and monitoring of these contaminants in fish across space and time can be confounded by size covariation. To account for this, size-standardization of contaminant concentrations within fish samples is a common practice. Standardized concentrations are often estimated using within-sample regression models, also known as power series regression (referred to here as sampling event regressions, or SERs). This approach requires higher sample sizes than mixed effect models (MEMs), which are suited for this application but are not as commonly used. Herein we compare SERs to three MEM approaches; restricted maximum likelihood, Bayesian inference via Markov chain Monte Carlo (MCMC), and approximate Bayesian inference with nested Laplace approximation (INLA). We did this for two contaminants …” authors:
- E_Smenderovac
- B_Kielstra
- Calvin Kluke
- Thomas A Johnston
- Satyendra P Bhavsar
- Robert Mackereth
- Stephanie Melles
- Gretchen L Lescord
- E_Emilson featured: false projects: [] publication: ‘Environmental Science & Technology’ publication_short: '' publication_types:
- “2” date: ‘2025-03-04T00:00:00Z’ publishDate: ‘2025-03-07’ title: ‘Mixed Model Approaches Can Leverage Database Information to Improve the Estimation of Size-Adjusted Contaminant Concentrations in Fish Populations’ url_pdf: “https://pubs.acs.org/doi/full/10.1021/acs.est.4c10303" url_source: “https://pubs.acs.org/doi/abs/10.1021/acs.est.4c10303"
Emily Smenderovac
Watershed Ecologist
Trained in microbial ecology and bioinformatic analysis of community datasets.
Brian Kielstra
Cumulative Effects Research Scientist
I am a landscape/aquatic ecologist generally interested in the cumulative effects of landscape pattern and process on recipient waters
Erik J.S. Emilson
Research Scientist, Watershed Ecology Team Lead, Associate Editor CJFR
I am interested in how forests support freshwater ecosystem services. My research combines microbial and molecular approaches to undertand how forest productivity and disturbances affect ecosystem functions in headwater streams and lakes.