From home range dynamics to population cycles: Validation and realism of a common vole population model for pesticide risk assessment

• Published in: Integrated Environmental Assessment and Management
• Main Author: Wang, Magnus
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2013
• Subjects: Common vole; Microtus arvalis
• Online Access: http://dx.doi.org/10.1002/ieam.1377; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fieam.1377; https://setac.onlinelibrary.wiley.com/doi/pdf/10.1002/ieam.1377

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 demonstrate how population models can be validated in great detail based on published data. The model is developed for application in pesticide risk assessment, therefore, the validation covers all areas of the biology of the common vole that are relevant for the analysis of potential effects and recovery after application of pesticides. Our results indicate that reproduction, survival, age structure, spatial behavior, and population dynamics reproduced from the model are comparable to field observations. Also interannual population cycles, which are frequently observed in field studies of small mammals, emerge from the population model. These cycles were shown to be caused by the home range behavior and dispersal. As observed previously in the field, population cycles in the model were also stronger for longer breeding season length. Our results show how validation can help to evaluate the realism of population models, and we discuss the importance of taking field methodology and resulting bias into account. Our results also demonstrate how population models can help to test or understand biological mechanisms in population ecology. Integr Environ Assess Manag 2013; 9: 294–307. © 2012 SETAC