Modelling the effects of ionising radiation on a vole population from the Chernobyl Red forest in an ecological context

Citation

i Batlle JV, Sazykina T, Kryshev A, Wood MD, Smith K, Copplestone D & Biermans G (2020) Modelling the effects of ionising radiation on a vole population from the Chernobyl Red forest in an ecological context. Ecological Modelling, 438, Art. No.: 109306. https://doi.org/10.1016/j.ecolmodel.2020.109306

Abstract
A novel mathematical model was developed to study the historical effects of ionising radiation from the 1986 Chernobyl accident on a vole population. The model uses an ecosystem approach combining radiation damages and repair, life history and ecological interactions. The influence of reproduction, mortality and factors such as ecosystem resource, spatial heterogeneity and migration are included. Radiation-induced damages are represented by a radiosensitive ‘repairing pool’ mediating between healthy, damaged and radio-adapted animals. The endpoints of the model are repairable radiation damage (morbidity), impairment of reproductive ability and mortality. The focus of the model is the Red Forest, an area some 3 km west of the Chernobyl Nuclear Power Plant. We simulated ecosystem effects of both current exposures and historical doses, including transgenerational effects and adaptation. The results highlight the primary role of animal mobility in stabilising the vole population after the accident, the importance of ecosystem recovery, the time evolution of the repairing and fecundity pools and the impact of adaptation on population sustainability. Using this model, we found dose rate tipping points for mortality and morbidity, along with a limiting migration rate for population survival and a limiting size of the most contaminated region needed not entailing loss of survival. Our ecosystem approach to radioecological modelling enables an exploration of the impact of radiation in an ecological context, consistent with the available observations. Model predictions indicate that population sensitivity in this exposure scenario does not contradict the benchmarks currently considered in risk assessments for wildlife. The model can be used to support advice on the extent to which historical doses and other ecological factors may influence different exposure modelling scenarios. The approach could easily be adapted to accommodate other stressors, thereby contributing to the evaluation of other regulatory benchmarks used in non-radiological risk assessment.

Keywords
Ecological Modelling

Journal
Ecological Modelling: Volume 438

• Accepted Final Documents Vives Et Al 2020