Modeling radionuclide Cs and C dynamics in an artificial forest ecosystem in Japan -FoRothCs ver1.0-

Predicting the environmental fate of Cs radionuclides in forest ecosystems is important for the effective management and assessment of radioactively contaminated forest areas. A large proportion of the radioactively contaminated areas in Japan consist of forest ecosystems, and most of these areas are artificial forests that are used for timber production (e.g., Japanese cedar (Cryptomeria japonica) and red pine (Pinus densiflora)). Determining the long-term redistribution of 137Cs in forest ecosystems is important for estimating human doses and understanding the ecological impacts and challenges associated with managing contaminated forests. To facilitate the management and 137Cs decontamination of these forests, we developed a new open-source 137Cs cycling model, ForRothCs, that considers C cycling within forests, as well as biomass production and soil decomposition processes. For the 137Cs inventory, this model estimates the dynamics (Bq m−2) and activity (Bq kg−2) of 137Cs on a decadal time scale, primarily in the leaves, branches, stems, litter layer, and the soil. This model is based on the biomass production and the dynamics of the C cycle models. We tested the model by considering a simple scenario of forest management, i.e., thinning and harvesting, for the first five years following a fallout event. The results showed that these activities have a limited impact on the 137Cs inventory due to the rapid migration of 137Cs from vegetation to soil. Our projections also showed the examined forest management practices resulted in reduced litterfall, which in turn reduced C input to the forest floor and increased the concentration of 137Cs in the litterfall and soil organic layer. Although further validation of the ForRothCs model is required using field observation data, the model can be used to evaluate long-term 137Cs dynamics associated with commonly used forest and decontamination management scenarios.

Abstract licence: CC BY

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