The pros and cons of ecological risk assessment based on data from different levels of biological organization

Abstract

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g. biomarkers), individual, population, community, ecosystem, and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study, and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

Ecological risk assessment of perfluooroctane sulfonate to aquatic fauna from a bayou adjacent to former fire training areas at a US Air Force installation

“…Additional chronic toxicity data would be helpful in refining the SSD and other toxicity benchmarks because it is worth noting that the value from the Keiter et al () study is approximately a factor of 5 lower than the next lowest toxicity value (2.3 μg/L, from MacDonald et al ). It is also worth mentioning that a criticism that can be levied against the approaches used in the present study to estimate risk is that we did not consider species interactions, environmental variation, or other “context dependencies” that can significantly alter the risk profile (Rohr et al ). It seems reasonable to conclude that at Barksdale Air Force Base there appears to be evidence to suggest a potential for an adverse effect from PFOS exposure, and additional, focused research may result in higher confidence risk estimates.…”

Consistent Effects of Pesticides on Community Structure and Ecosystem Function in Freshwater Systems

“…Ecological risk assessment, made complex by tens of thousands of synthetic chemicals and diverse species assemblages, could be simplified by assessing groups of chemicals that share similar chemical structures or environmental targets and examining responses of functional groups of taxa ( 14 ). A similar approach is taken by Quantitative Structure-Activity Relationships (QSAR) ( 15 ), which attempts to assess toxicity of synthetic chemicals using information on compound structure.…”

Atrazine and amphibians: Data re-analysis and a summary of the controversy

“…Clearly, there is a need to understand how climate change will affect exposure and toxicity of atrazine and other chemical contaminants (Rohr et al 2013a, Landis et al 2014). Nevertheless, interactions among chemical contaminants or between chemical contaminants and non-chemical stressors are unfortunately rarely considered in most ecological risk assessments of chemicals (Rohr et al 2016, 2017).…”