A probabilistic approach to chronic effects assessments for listed species in a vernal pool case study
Authors: Oliver Leah , Sinnathamby Sumathy , Purucker Steven , Raimondo Sandy 
Published: May 2024

Ecological risk assessments for potential pesticide impacts on species listed as threatened or endangered must ensure that decisions to grant registration or establish water quality standards will not jeopardize species or their critical habitats. Pesticides are designed to affect pest species via physiological pathways that may be shared by some nontarget species for which toxicity data are usually unavailable, creating a need for robust methods to estimate acute and chronic toxicity with minimal data. We used a unique probabilistic approach to estimate the risk of chronic effects of two organophosphate (OP) pesticides on the vernal pool fairy shrimp Branchinecta lynchi. Acute toxicity estimates were derived from Monte Carlo (MC) sampling of acute toxicity distributions developed from interspecies relationships using surrogate species. Within each MC draw, acute values were divided by an acute to chronic ratio (ACR) sampled from a distribution of ACRs for OP pesticides and invertebrates, producing a distribution of chronic effects concentrations. The estimated exposure concentrations (EECs) were sampled from distributions representing different environmental conditions. Risk was characterized using probability distributions of acute toxicity, ACRs, and EECs in a probabilistic analysis, as well as partial probabilistic variations that used only some distributions whereas some variables were used deterministically. A deterministic risk quotient (RQ) was compared with the results of probabilistic methods to compare the approaches. Risk varied across exposure scenarios and the number of variables that were handled probabilistically, increasing as the number of variables drawn from distributions increased. The magnitude of RQs was not correlated with the probability that EECs would exceed chronic thresholds, and comparison of the two approaches demonstrates the limited interpretability of RQs. Our novel probabilistic approach to estimating chronic risk with minimal data incorporates uncertainty underlying both exposure and effects assessments for listed species. Integr Environ Assess Manag 2024;20:1654–1666. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

Key Points

Chronic risk estimates are important for ecological risk assessments (ERAs), and we present a novel approach to evaluating chronic risk using minimal data incorporating the distributions of effects and environmental exposure concentrations. Ecological risk assessment for pesticides potentially affecting a listed vernal pool fairy shrimp species is used as a case study to demonstrate our approach that is applicable to ERAs in general. Probabilistic approaches incorporate real-world uncertainty into the effects and exposure assessments for ERAs required by different regulatory authorities. Protection of listed species from jeopardy under the Endangered Species Act will benefit from the application of probabilistic approaches to ERAs that consider variability and uncertainty in effects and environmental exposure concentrations.