An example of population‐level risk assessments for small mammals using individual‐based population models
This article presents a case study demonstrating the application of 3 individual‐based spatially explicit population models (IBMs, also known as agent‐based models) in ecological risk assessments to predict long‐term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of the FungicideX was defined so that the deterministic long‐term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e. higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all three cases low population sensitivity unless FungicideX was applied at very high (x10) rates. Recovery from local population impacts was fast and only in cases of patch extinction and recolonization, occurring when simulating intentionally high acute toxic effects, recovery periods were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. This article is protected by copyright. All rights reserved
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