Integrating Empirical Ecotoxicology and Predictive Modelling to Assess Ecological and Human Health Risks from Heavy Metals in Malaysia's Chini Lake UNESCO Biosphere Reserve.

Empirical ecotoxicology reveals high ecological risks from heavy metals in Chini Lake, Malaysia, which are underestimated by predictive models like ECOSAR.

• Why it matters: Accurate risk assessment of heavy metal contamination is essential for conserving freshwater ecosystems and informing policy, especially in areas affected by legacy mining and land-use changes.
• What they did: The study combined empirical (ECOTOX) and predictive (ECOSAR) toxicity data across 18 sampling stations, analyzing heavy metal concentrations, pollution indices, and risk metrics such as RQ and HQ.
• The result: Empirical data indicated high ecological risks (RQ ≥ 1) from aluminium, zinc, copper, nickel, and lead, while predictive models underestimated these threats; human health risks from arsenic and cadmium were present mainly for children, emphasizing the need for field-based data to guide sustainable water management.