Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish

Abstract

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Effects of industrial pollution on the reproductive biology of Squalius laietanus (Actinopterygii, Cyprinidae) in a Mediterranean stream (NE Iberian Peninsula)

“…However, it is unclear how these effects may affect fish populations in the wild (Mintram et al 2018). The main inconvenient of most laboratory studies is that they do not fully reproduce natural conditions and/or do not consider the potential synergy of mixtures of contaminants.…”

Understanding and managing fish populations: keeping the toolbox fit for purpose

“…The use of IBMs in fish research has grown exponentially (DeAngelis & Mooij, ) as computational power has increased (DeAngelis & Grimm, ). Several IBMs were presented at the 50th Anniversary Symposium of The Fisheries Society of the British Isles, and with continued increases in computational power, IBMs look set to offer powerful new avenues for population research (DeAngelis & Grimm, ) in computationally challenging multifactor systems such as fish ecotoxicology (Mintram et al, ). Additionally, a variety of tools now exist which provide for the easier creation of new models, such as various R packages (http://www.r-project.org) and programmable environments ( e.g .…”

Assessing the population relevance of endocrine‐disrupting effects for nontarget vertebrates exposed to plant protection products

“…The concept of focal species has been adopted most fully for birds and mammals in PPP assessment, although the concept has wider application for other vertebrate taxa and has also been explored for fish (Ibrahim et al ), amphibians, and reptiles (EFSA PPR ). Mintram et al (), in a review of modeling approaches for risk assessment of endocrine disruptors in fish, recommend that “the development of future models should include species representing a range of life‐histories and…their selection should be guided by the derivation of ecological scenarios which are relevant to major land use and water body types in which chemical exposures and effects are predicted according to current risk assessments.”…”

“…There are established methods to demonstrate the relevance of effects with population models to extrapolate from the laboratory to the field (e.g., Wang ; Liu et al ; Schmitt et al ; Topping and Elmeros ; Topping and Weyman ). Mintram et al () reviewed modeling approaches potentially applicable to the environmental risk assessment of endocrine‐active substances in fish and concluded that individual‐based models (IBMs) are a particularly useful model type because they can account for species‐specific traits and behaviors (e.g., breeding behaviors) and simulate interorganism interactions and organism–environment interactions (including responses to chemical exposure). IBMs therefore capture both the direct and indirect population‐level effects of chemical exposures.…”

“…IBMs therefore capture both the direct and indirect population‐level effects of chemical exposures. Mintram et al () identify the main challenge as striking a balance between site‐specific versus generic applicability, because of the often complex and environmentally plastic life histories of fish.…”