An individual-based approach to model spatial population dynamics of invertebrates in aquatic ecosystems after pesticide contamination

Abstract

In the present study we present a population model (Metapopulation model for Assessing Spatial and Temporal Effects of Pesticides [MASTEP]) describing the effects on and recovery of the waterlouse Asellus aquaticus after exposure to a fast‐acting, nonpersistent insecticide as a result of spray drift in pond, ditch, and stream scenarios. The model used the spatial and temporal distribution of the exposure in different treatment conditions as an input parameter. A dose–response relation derived from a hypothetical mesocosm study was used to link the exposure with the effects. The modeled landscape was represented as a lattice of 1‐ by 1‐m cells. The model included processes of mortality of A. aquaticus, life history, random walk between cells, density dependence of population regulation, and, in the case of the stream scenario, medium‐distance drift of A. aquaticus due to flow. All parameter estimates were based on expert judgment and the results of a thorough review of published information on the ecology of A. aquaticus. In the treated part of the water body, the ditch scenario proved to be the worst‐case situation, due to the absence of drift of A. aquaticus. Effects in the pond scenario were smaller because the pond was exposed from one side, allowing migration from the other, less contaminated side. The results of the stream scenario showed the importance of including drift for the population recovery in the 100‐m stretch of the stream that was treated. It should be noted, however, that the inclusion of drift had a negligible impact on numbers in the stream as a whole (600 m).

Preliminary risk assessment of common-use pesticides using PRIMET and PERPEST pesticide risk models in a semi-arid subtropical region

“…There are various models being used to predict ecological risk of pesticides, including population, food-web and ecological models (Koelmans et al, 2001;Traas et al, 1998;Van den Brink et al, 2007). However, these models are quite often intricate and complex with a large number of input parameters required.…”

“…Quite often the detailed data needed for these models are not available, and the models often focus only on certain risk aspects, making their applicability limited. The resulting outcome of this is complex simulation models that are inaccurate due to the primary input data being insufficient (Van den Brink et al, 2006). This is amplified in developing countries due to a lack of resources, thus restricting widespread use of the models (London et al, 2005).…”

“…This review formed the basis of the PERPEST database. The higher-tier risk model used in the preliminary risk assessment is the PERPEST model ( Van den Brink et al, 2002;Van Nes and Van den Brink, 2003;Van den Brink et al, 2006). PERPEST predicts the potential toxic effects of a specific pesticide concentration on various grouped endpoints using a case-based reasoning (CBR) approach.…”

“…The endpoints used for predicting effects on insecticides are: algae and macrophytes, rotifers, insects, micro-crustaceans, macro-crustaceans, other invertebrates, fish and community metabolism. Macrophytes, periphyton, phytoplankton, zooplankton, insects, molluscs and macro-crustaceans, fish and tadpoles and community metabolism are the endpoints used for evaluating herbicides (Van den Brink et al, 2006). All of the endpoints are structural endpoints except for community metabolism which represents a functional endpoint.…”

CREAM: a European project on mechanistic effect models for ecological risk assessment of chemicals

“…Such understanding is crucial for improving risk mitigation strategies and ecosystem management. By MEMs, we mean both ecological models that mechanistically represent key ecological processes Pastorok et al 2002Pastorok et al , 2003van den Brink et al 2007;Preuss et al 2009b) and individual-level models quantifying adverse effects of chemicals on organisms based on mechanistic understanding (e.g., Ankley et al 1995;Jager and Kooijman 2005;Ashauer et al 2007). In these models, scenarios with and without effects of chemicals, for example, pesticides, on nontarget organisms are compared.…”