Screening indices for cadmium-contaminated soil using earthworm as bioindicator

Area of Science:

• Environmental toxicology
• Ecotoxicology
• Soil science

Background:

• Cadmium (Cd) contamination poses significant risks to soil ecosystems.
• Earthworms, like Eisenia fetida, are crucial soil invertebrates and sensitive indicators of environmental stress.
• Developing effective early warning systems for soil contamination is vital for environmental protection.

Purpose of the Study:

• To investigate the oxidative stress response in different parts of Eisenia fetida under varying cadmium exposure levels.
• To identify key monitoring indices for an early warning system for cadmium-contaminated soil.
• To differentiate short-term and long-term stress responses and their corresponding biomarkers.

Main Methods:

• Artificial soil simulation tests were conducted with Eisenia fetida exposed to a gradient of cadmium concentrations (0-500 mg/kg).
• Earthworms were divided into head and tail sections to analyze oxidative stress indices.
• Factor analysis and analytic hierarchy process were employed to establish a mathematical model for screening monitoring indices.
• Short-term (10 days) and long-term (30 days) exposure groups were analyzed.

Main Results:

• Total protein (TP) was a key indicator in earthworm head tissues during short-term stress (3-4 and 8-9 days).
• TP in tail tissues was significant for monitoring on days 2, 4, 6, and 8-10.
• Catalase (CAT) and peroxidase (POD) were important early indicators, particularly in the first week.
• In long-term tests, glutathione peroxidase (GPX) in the head and TP in the tail were key after 10 days, with TP (head) and malondialdehyde (MDA) (tail) being crucial at 20-30 days.

Conclusions:

• Specific oxidative stress biomarkers in Eisenia fetida tissues can effectively indicate early cadmium soil contamination.
• The identified key monitoring indices vary between earthworm tissues (head vs. tail) and exposure duration (short-term vs. long-term).
• This research provides a foundation for developing a robust mathematical model for a cadmium-contaminated soil early warning system using earthworm biomarkers.