2013
DOI: 10.1002/ieam.1377
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From home range dynamics to population cycles: Validation and realism of a common vole population model for pesticide risk assessment

Abstract: Despite various attempts to establish population models as standard tools in pesticide risk assessment, population models still receive limited acceptance by risk assessors and authorities in Europe. A main criticism of risk assessors is that population models are often not, or not sufficiently, validated. Hence the realism of population-level risk assessments conducted with such models remains uncertain. We therefore developed an individual-based population model for the common vole, Microtus arvalis, and dem… Show more

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Cited by 18 publications
(17 citation statements)
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“…Murphy et al 2017). Scaling-up high-resolution IBMs to explore range dynamics can present computational challenges, particularly for widespread species (Wang 2013;Li enard & Strigul 2016).…”
Section: Demographic Distribution Models (Ddm)mentioning
confidence: 99%
“…Murphy et al 2017). Scaling-up high-resolution IBMs to explore range dynamics can present computational challenges, particularly for widespread species (Wang 2013;Li enard & Strigul 2016).…”
Section: Demographic Distribution Models (Ddm)mentioning
confidence: 99%
“…49 Population modelling approaches indicate that cycle amplitude can be related to variations in the length of the breeding season wileyonlinelibrary.com/journal/ps and movement patterns of common voles. 55 Individual-based models have been developed for risk assessment in wood mice (Apodemus sylvaticus) 56 and common voles, 55 and agent-based models have been proposed. 57 Such models may be helpful tools for risk assessment if they are based on sound knowledge and successful validation for all required scenarios.…”
Section: Common Vole Biology and Population Dynamicsmentioning
confidence: 99%
“…Increased computational power and agreement on probabilistic risk paradigms allowed regional scale assessments to emerge (Solomon et al 1996Purucker et al 2007). Recent models may incorporate more refined predictions of exposures and effects across landscapes (Schmolke et al 2010;Dixon 2012;Bartell et al 2013;Kohler and Triebskorn 2013;Van den Brink 2013;Wang 2013;Focks et al 2014;Topping et al 2015;Dohmen et al 2016;Hilbers et al 2018). These approaches allow prediction of population exposures to pesticides and resultant responses without having to conduct painstaking multiyear field assessments of population dynamics.…”
Section: Examples Of Higher Tier Effects and Exposure Refinements Formentioning
confidence: 99%