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Estimating risks to aquatic life using quantile regression

Freshwater Science

By:
, , and
DOI: 10.1899/11-133.1

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Abstract

One of the primary goals of biological assessment is to assess whether contaminants or other stressors limit the ecological potential of running waters. It is important to interpret responses to contaminants relative to other environmental factors, but necessity or convenience limit quantification of all factors that influence ecological potential. In these situations, the concept of limiting factors is useful for data interpretation. We used quantile regression to measure risks to aquatic life exposed to metals by including all regression quantiles (τ  =  0.05–0.95, by increments of 0.05), not just the upper limit of density (e.g., 90th quantile). We measured population densities (individuals/0.1 m2) of 2 mayflies (Rhithrogena spp., Drunella spp.) and a caddisfly (Arctopsyche grandis), aqueous metal mixtures (Cd, Cu, Zn), and other limiting factors (basin area, site elevation, discharge, temperature) at 125 streams in Colorado. We used a model selection procedure to test which factor was most limiting to density. Arctopsyche grandis was limited by other factors, whereas metals limited most quantiles of density for the 2 mayflies. Metals reduced mayfly densities most at sites where other factors were not limiting. Where other factors were limiting, low mayfly densities were observed despite metal concentrations. Metals affected mayfly densities most at quantiles above the mean and not just at the upper limit of density. Risk models developed from quantile regression showed that mayfly densities observed at background metal concentrations are improbable when metal mixtures are at US Environmental Protection Agency criterion continuous concentrations. We conclude that metals limit potential density, not realized average density. The most obvious effects on mayfly populations were at upper quantiles and not mean density. Therefore, we suggest that policy developed from mean-based measures of effects may not be as useful as policy based on the concept of limiting factors.

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Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Estimating risks to aquatic life using quantile regression
Series title:
Freshwater Science
DOI:
10.1899/11-133.1
Volume
31
Issue:
3
Year Published:
2012
Language:
English
Publisher:
The Society for Freshwater Science
Contributing office(s):
Fort Collins Science Center
Description:
15 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Freshwater Science
First page:
709
Last page:
723
Country:
United States
State:
Colorado