Adding Value to Ecological Risk Assessment with Population Modeling

Forbes, Valery E.; Calow, Peter; Grimm, Volker; Hayashi, Takehiko I.; Jager, Tjalling; Katholm, Agnete Krabbe; Palmqvist, Annemette; Pastorok, Robert A.; Salvito, D.; Sibly, Richard M.; Spromberg, Julann A.; Stark, John D.; Stillman, Richard A.

doi:10.1080/10807039.2011.552391

Cited by 91 publications

(79 citation statements)

References 35 publications

(32 reference statements)

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“…Models are classically used to upscale effects from individual level to population level (Forbes et al 2009;Forbes et al 2011). Our model could also be used in this purpose.…”

Section: Population Modelling In Ecotoxicologymentioning

confidence: 99%

Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki)

Beaudouin

Ginot

Monod³

2011

Ecotoxicology

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Experimental ecosystems such as mesocosms have been developed to improve the ecological relevance of ecotoxicity test. However, in mesocosm studies, the number of replicates is limited by practical and financial constraints. In addition, high levels of biological organization are characterized by a high variability of descriptive variables. This variability and the poor number of replicates have been recognized as a major drawback for detecting significant effects of chemicals in mesocosm studies. In this context, a tool able to predict precisely control mesocosms outputs, to which endpoints in mesocosms exposed to chemicals could be compared should constitute a substantial improvement. We evaluated here a solution which consists in stochastic modelling of the control fish populations to assess the probabilistic distributions of population endpoints. An individual-based approach was selected, because it generates realistic fish length distributions and accounts for both individual and environmental sources of variability. This strategy was applied to mosquitofish (Gambusia holbrooki) populations monitored in lentic mesocosms. We chose the number of founders as a so-called "stressor" because subsequent consequences at the population level could be expected. Using this strategy, we were able to detect more significant and biologically relevant perturbations than using classical methods. We conclude that designing an individual-based model is very promising for improving mesocosm data analysis.This methodology is currently being applied to ecotoxicological issues.

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“…Models are classically used to upscale effects from individual level to population level (Forbes et al 2009;Forbes et al 2011). Our model could also be used in this purpose.…”

Section: Population Modelling In Ecotoxicologymentioning

confidence: 99%

Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki)

Beaudouin

Ginot

Monod³

2011

Ecotoxicology

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“…Quantitative definitions of the terms "impairment," "unacceptable," "undesirable," "harmful" or "adverse" are generally lacking in chemical regulations and supporting guidance documents for prospective ERA (Tables 2 and 5). For the majority of chemicals, the significance of population-level effects, required for deriving PNECs or RACs, is based on statistically significant laboratory effects data for individual test organisms, rather than on ecologically significant effects measured or predicted for wild populations (Forbes et al 2008(Forbes et al , 2011Brown et al 2014). The ERA of PPPs also includes the option for appropriate assessments under field conditions of the population density and viability of nontarget species (including keystone and/or indicator species), biodiversity (e.g., overall species richness of ecological communities), and ecosystem services (EFSA 2013a).…”

Section: Quantitative Definitions Of Adverse Effectsmentioning

confidence: 99%

Toward the definition of specific protection goals for the environmental risk assessment of chemicals: A perspective on environmental regulation in Europe

Brown

Whale

Jackson

et al. 2016

Integr Envir Assess & Manag

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“…Since then, various models describing different levels of biological organization have proved to be powerful tools for extrapolating impacts of chemicals across levels and scales [3,[38][39][40][41]. Recently, key scientific and regulatory organizations have advocated the use of mechanistic effects models in ERA [42][43][44][45].…”

Section: The Key Role Of Mechanistic Effects Modelsmentioning

confidence: 99%

“…The utility of mechanistic effects models in ERA was recognized in the mid-1980s and early 1990s [37], but this type of model was not adopted by risk assessors in toxic chemical regulatory programs at that time. Since then, various models describing different levels of biological organization have proved to be powerful tools for extrapolating impacts of chemicals across levels and scales [3,[38][39][40][41]. Recently, key scientific and regulatory organizations have advocated the use of mechanistic effects models in ERA [42][43][44][45].…”

Section: The Key Role Of Mechanistic Effects Modelsmentioning

confidence: 99%

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A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

Forbes¹,

Salice

Birnir

et al. 2017

Enviro Toxic and Chemistry

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Abstract-Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. Environ Toxicol Chem 2017;36:845-859. # 2017 SETAC Keywords-Ecological production function; Ecological risk assessment; Ecosystem service; Environmental management; Mechanistic effects model Challenges for Ecological Risk Assessment and ManagementThe primary goal of ecological risk assessment (ERA) of chemicals is to provide defensible science-based support for environmental management decisions. This involves making explicit connections between impacts on the benefits derived by people from ecosystems (so-called ecosystem services [1]) and the costs of managing the causes of those impacts. At the core of this approach is the need for relevant chemical exposure-response relationships. However, current ERA approaches often fall short in these regards because methods In This Issue: ET&C FOCUSFocus articles are part of a regular series intended to sharpen understanding of current and emerging topics of interest to the scientific community. for estimating and integrating exposure and effects are often based on overly simplistic assumptions [2,3]. For example, measures of organism-level toxicity (e.g., 50% effect concentrations) are used as indicators of population-level impacts of chemicals. A primary concern is that the kinds of information collected to support ERAs are far removed from the kinds of ecological entities (e.g., species or habitats) that are the targets of protection, which themselves are often only vaguely defined in legislation (e.g., European pesticides legislation refers to "no unacceptable effects on the environment"). In practice, protection goals for ecological systems are (implicitly or explicitly) often at the population, community, or ecosystem level (e.g., persistence or abundance of a p...

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Adding Value to Ecological Risk Assessment with Population Modeling

Cited by 91 publications

References 35 publications

Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki)

Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki)

Toward the definition of specific protection goals for the environmental risk assessment of chemicals: A perspective on environmental regulation in Europe

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

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