Sandy Raimondo

W Matthew Henderson, Cheryl Hankins, Sandy Raimondo; Significant research needs for defensible hazard assessment of UV Filters in aquatic ecosystems Part 2

Coral reefs are declining globally as a result of multiple stressors, including land-based stressors, such as sedimentation and pollution, and those that are related to a changing climate, such as increases in ocean acidification. Degradation of US Caribbean coral reef biota has been associated with exposure to sewage effluent from wastewater treatment plants (WWTPs). The Puerto Rico Aqueduct and Sewer Authority (PRASA) maintains WWTPs on the north coast of Puerto Rico, which release effluent into the marine environment in the vicinity of coral reefs. Using data collected by PRASA surveys conducted from 1999 to 2013, we examined coral reef condition at survey sites to identify potential changes or differences in reefs with respect to their proximity to the WWTP effluent pipes (e.g., upstream, downstream). The proportion of coverage represented by all coral, sensitive taxa, and tolerant taxa were compared across sites located upstream and downstream of WWTP effluent pipes using multivariate approaches and analysis of variance. The proportion of healthy, sensitive coral species and invasive or tolerant coral species were not different at sites downstream of the WWTP effluent pipe compared to upstream. These results are caveated by the limited sampling design, highly variable communities across WWTP locations, and the sparsity or absence of well-developed coral reef communities at most stations. We evaluate the strengths and weaknesses of the survey design and provide recommendations for future coral reef surveys investigating potential impacts of WWTP effluent.

Vernal pool fairy shrimp, Branchinecta lynchi, is a freshwater crustacean endemic to California and Oregon, including California’s Central Valley. B. lynchi is listed as a Federally Threatened species under the US Endangered Species Act, and as a vulnerable species on the IUCN Red List. Threats that may negatively impact vernal pool fairy shrimp populations include pesticide applications to agricultural land use (e.g., agrochemicals such as organophosphate pesticides) and climate changes that impact vernal pool hydrology. Pop-GUIDE (Population model Guidance, Use, Interpretation, and Development for Ecological risk assessment) is a comprehensive tool that facilitates development and implementation of population models for ecological risk assessment and can be used to document the model derivation process. We employed Pop-GUIDE to document and facilitate the development of a population model for investigating impacts of organophosphate pesticides on vernal pool fairy shrimp populations in California’s Central Valley. The resulting model could be applied in combination with field assessment and laboratory-based chemical analysis to link effects from pesticide exposure to adverse outcomes in populations across their range. B. lynchi has a unique intra-annual life cycle that is largely dependent upon environmental conditions. Future deployment of this population model should include complex scenarios consisting of multiple stressors, whereby the model is used to examine scenarios that combine chemical stress resulting from exposure to pesticides and climate changes.

Under standard guidance for conducting Ecological Risk Assessments (ERAs), the risks of chemical exposure to diverse organisms are most often based on deterministic point estimates evaluated against safety-factor-based levels of concern (LOCs). While the science and guidance for mechanistic effect models (e.g., demographic, population, and agent-based) have long been demonstrated to provide more ecologically relevant effect endpoints upon which risk can be evaluated, their application in ERAs has been limited, particularly in the US. This special issue highlights the state of the science in effect modeling for ERAs through demonstrated application of the recently published Population modeling Guidance, Use, Interpretation, and Development for ERA (Pop-GUIDE). We introduce this issue with a perspective on why it is critical to move past the current application of deterministic endpoints and LOCs. We demonstrate how the current, widely used approaches contain extensive uncertainty that could be reduced considerably by applying models that account for species life histories and other important endogenous and exogenous factors critical to species sustainability. We emphasize that it is long past time to incorporate better, more robust, and ecologically relevant effect models into ERAs, particularly for chronic risk determination. The papers in this special issue demonstrate how mechanistic models that follow Pop-GUIDE better inform ERAs compared to the current standard practice.

The assimilation of population models into ecological risk assessment (ERA) has been hindered by their range of complexity, uncertainty, resource investment, and data availability. Likewise, ensuring that the models address risk assessment objectives has been challenging. Recent research efforts have begun to tackle these challenges by creating an integrated modeling framework and decision guide to aid the development of population models with respect to ERA objectives and data availability. In the framework, the trade-offs associated with the generality, realism, and precision of an assessment are used to guide the development of a population model commensurate with the protection goal. The decision guide provides risk assessors with a stepwise process to assist them in developing a conceptual model that is appropriate for the assessment objective and available data. We have merged the decision guide and modeling framework into a comprehensive approach, Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE), for the development of population models for ERA that is applicable across regulatory statutes and assessment objectives. In Phase 1 of Pop-GUIDE, assessors are guided through the trade-offs of ERA generality, realism, and precision, which are translated into model objectives. In Phase 2, available data are assimilated and characterized as general, realistic, and/or precise. Phase 3 provides a series of dichotomous questions to guide development of a conceptual model that matches the complexity and uncertainty appropriate for the assessment that is in concordance with the available data. This phase guides model developers and users to ensure consistency and transparency of the modeling process. We introduce Pop-GUIDE as the most comprehensive guidance for population model development provided to date and demonstrate its use through case studies using fish as an example taxon and the US Federal Insecticide Fungicide and Rodenticide Act and Endangered Species Act as example regulatory statutes. Integr Environ Assess Manag 2021;17:767–784. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA. KEY POINTS The assimilation of population models into the ecological risk assessment (ERA) process has been hindered by their range of complexity, uncertainty, resource investment, and data availability, and translating model outputs into endpoints that can be used by risk assessors has been challenging. We present Population modeling Guidance, Use, Interpretation, and Development for Ecological Risk Assessment (Pop-GUIDE) as a comprehensive approach for the development of population models for ERA that is applicable across regulatory statutes, assessment objectives, and taxa. Pop-GUIDE uses the trade-offs associated with the generality, realism, and precision of an assessment to guide the development of a population model commensurate with ERA protection goal using a multiphase process. Two case studies demonstrate the application of Pop-GUIDE for fish and the pesticide chlorpyrifos under different assessment objectives.

Ecological risk assessment is challenged by the need to assess hazard to the diverse communities of organisms inhabiting aquatic and terrestrial systems. Computational approaches, such as Quantitative Structure Activity Relationships (QSAR) and Interspecies Correlation Estimation (ICE) models, are useful tools that provide estimates of acute toxicity where data are lacking or limited for ecological risk assessments (ERA). This review describes the technical basis of ICE models for use in pesticide ERA that may be used in conjunction with QSAR model estimates or surrogate species toxicity data and demonstrates the potential for improving hazard assessment. Validation and uncertainty analysis of ICE model predictions are summarized and used as guidance for selecting ICE models and evaluating toxicity predictions. A user-friendly web-based ICE modelling platform (Web-ICE) is described and demonstrated through case studies. Case studies include the development of Species Sensitivity Distributions generated from QSAR and ICE estimates, comparative sensitivity for a pesticide and its degradate, and application of ICE-estimated toxicity values for listed species assessments.