Theoretical interpretation of ecological observations of the Chernobyl Exclusion Zone: application of the...

Ecological observations in the Chernobyl Exclusion Zone (CEZ) show that populations of large mammals, such as wolves, boars, and elks, have recovered and remain stable despite chronic exposure to radiation. This study applies the Whack-A-Mole (WAM) model-a dynamic, dose-rate-dependent mathematical model-to the CEZ environment to explain the observed ecological stability under persistent low-dose-rate exposure that conventional Linear Non-Threshold (LNT) models fail to predict.

The WAM model explicitly incorporates removal processes of radiation-induced mutated cells, allowing evaluation of mutation frequency at steady state under chronic exposure. Using standardized parameters calibrated across species and reported dose rates from wolf tracking studies (external 10-35 mGy/y; internal + external up to 87 mGy/y), we calculated the time evolution and equilibrium values of mutation frequency in mammalian cells.

The equilibrium value of the mutation frequency increased as the radiation dose increased. This increase, however, remained below 1% of the natural baseline even under the upper-end CEZ exposure (87 mGy/y). At mean (18.4 mGy/y) and maximum (35.9 mGy/y) external dose rates, increases were only +0.18% and +0.35%, respectively. The boundary between LNT-like linear behavior and WAM saturation occurred around 330 hours regardless of dose rate. In contrast, the LNT model predicts mutation accumulation at levels incompatible with the continued growth of wolf populations, contradicting ecological observations in the CEZ.

The WAM model characterizes the dynamics of mutation frequency under chronic exposure and provides a mechanistic interpretation compatible with the absence of population-level health effects observed in the CEZ. Observed molecular responses, including endogenous retrovirus (ERV) activation and immune alterations, represent functioning repair and removal mechanisms rather than pathological damage.