title: Next-generation ecological risk assessment: Predicting risk from molecular initiation to ecosystem service delivery.
abstract: Ecological risk assessment is the process of evaluating how likely it is that the environment may be impacted as the result of exposure to one or more chemicals and/or other stressors. It is not playing as large a role in environmental management decisions as it should be. A core challenge is that risk assessments often do not relate directly or transparently to protection goals. There have been exciting developments in in vitro testing and high-throughput systems that measure responses to chemicals at molecular and biochemical levels of organization, but the linkage between such responses and impacts of regulatory significance - whole organisms, populations, communities, and ecosystems - are not easily predictable. This article describes some recent developments that are directed at bridging this gap and providing more predictive models that can make robust links between what we typically measure in risk assessments and what we aim to protect.
authors.affiliation: Department of Ecology, Evolution, and Behavior, College of Biological Sciences, 123 Snyder Hall, 1475 Gortner Ave, St. Paul, MN 55018, USA. Electronic address: veforbes@umn.edu.
authors.forename: Valery E
authors.initials: VE
authors.lastname: Forbes
authors.affiliation: Department of Ecology, Evolution, and Behavior, College of Biological Sciences, 123 Snyder Hall, 1475 Gortner Ave, St. Paul, MN 55018, USA. Electronic address: ngalic@umn.edu.
authors.forename: Nika
authors.initials: N
authors.lastname: Galic
mesh_terms: D003247:Conservation of Natural Resources; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D004785:Environmental Pollutants / Q000633:toxicity*; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods*
chemical_list: D004785:Environmental Pollutants
keywords: Adverse outcome pathways; Ecological protection goals; Ecosystem services; Environmental management; Mechanistic effect models; Predictive systems models