The role of bioindicator plants in environmental forensics: Potential applications for detecting heavy metal pollution in agricultural landscapes

Abstract

Background: Heavy metal contamination in Indonesian agricultural lands poses serious risks to ecosystem stability, food security, and public health. Major sources include excessive application of chemical fertilizers and pesticides, as well as industrial and domestic waste. Bioindicator plants can detect heavy metal pollutants through absorption and accumulation in plant tissues. Integrating bioindicator approaches into environmental forensic studies may strengthen pollution detection and support sustainable land management. Methods: This study employed a literature review and secondary data analysis to examine the potential of bioindicator plants in supporting environmental forensic investigations of heavy metal contamination in agricultural soils. Findings: Common heavy metals identified in Indonesian agricultural lands include Pb, Cd, Zn, Cu, Fe, and Mn. Frequently studied bioindicator plants are Oryza sativa, Eichhornia crassipes, Ipomoea aquatica, Ficus benghalensis, and Pteris vittata. Existing national research primarily focuses on ecological monitoring and phytoremediation, while limited attention has been given to contamination tracing, source identification, standardized analytical methods, and integration with environmental forensic frameworks. This indicates significant methodological and conceptual gaps in applying bioindicator science for evidentiary and investigative purposes. Conclusion: Bioindicator plants have strong potential as scientific tools for detecting and tracing heavy metal contamination. Strengthening their integration into environmental forensic frameworks can enhance evidence-based pollution control and promote sustainable agricultural land management in Indonesia. Novelty/Originality of this Article: This study systematically positions bioindicator plants within an environmental forensic framework, moving beyond conventional ecological monitoring toward contamination tracing and evidentiary assessment, thereby providing a conceptual foundation for more reliable pollution detection strategies.