Population models in pesticide risk assessment: Lessons for assessing population‐level effects, recovery, and alternative exposure scenarios from modeling a small mammal

Abstract

In the last few years, the interest in using ecological population models as a tool for pesticide risk assessment has increased rapidly. Practical guidance, however, on how to perform a risk assessment with a population model is still lacking. It is still unclear which endpoint (population density, population growth, etc.) is the most sensitive indicator of population-level effects and how risk can be evaluated at the population level. Moreover, a main added value of model-based risk assessments, which is an understanding of the mechanisms involved in alternative exposure scenarios, so far has received little attention. We therefore used an example model to compare commonly used endpoints and alternative exposure scenarios. The model is a structurally realistic, but relatively simple, individual-based, spatially explicit model for the common shrew (Sorex araneus), which was selected because it has been tested and validated extensively. We show that population density is more sensitive for detecting population-level effects in the short term (months) than population growth rate. Population viability measured by extinction risk can also be a relevant endpoint, because it is especially sensitive for small populations. We show that landscape structure and the timing of pesticide application (population structure at the time of application) can have a great impact on population recovery, and we analyze statistical tests for use in population-level risk assessments. Our results demonstrate which factors and insights should be taken into account in population-level risk assessments.

Adverse outcome pathways and ecological risk assessment: Bridging to population‐level effects

“…A complete discussion about which population-level endpoints may be used and how risk assessments that incorporate population modeling shall be performed is beyond the scope of this article. For further discussion, refer to Barnthouse et al [7], Munns et al [21], Pastorok et al [22,23], Thorbek et al [24], or Wang and Grimm [25]. Each type of model serves to answer specific questions related to abundance, productivity, viability, extinction, and recovery while having different data requirements, assumptions, generality, realism, and regulatory applicability [21].…”

The role of ecological models in linking ecological risk assessment to ecosystem services in agroecosystems

“…In the realms of ERA, the added value of ecological models in obtaining more realistic assessments of risk has been argued (Forbes et al, 2008(Forbes et al, , 2009Thorbek et al, 2009;Galic et al, 2010;Schmolke et al, 2010a;Wang and Grimm, 2010). Several different modeling approaches have been applied specifically to questions related to chemical risk assessment Schmolke et al, 2010b); their development and use are not, however, restricted to the field of ERA.…”

Assessment of Chemical Pollution With Routine Pesticides Using PRIMET, a Pesticide Risk Model in the Benoe Stream in the South-West Region of Cameroon

“…In recent years, the interest in using ecological population models as a tool for pesticide risk assessment has increased rapidly (Wang and Grimm, 2010). Despite considerable increased pesticide use over the past decades, little research has been done into their fate and effects in surface waters in tropical regions (Daam and Brink , 2010).…”

“…It is still unclear which endpoint (population density, population growth, etc.) is the most sensitive indicator of population-level effects and how risk can be evaluated at the population level (Wang and Grimm, 2010). PRIMET (Pesticides Risks in the tropics to Man, Environment and Trade ) is a simple risk assessment model that requires few inputs and is suitable for use in developing countries (Peteers et al, 2008).This model has been used in two Asian countries (Thailand and Sri Lanka) and in South Africa (Malherbe et al, 2013).…”