Cumulative effects of chemical pollutants such as trace pesticides, pharmaceutical residues, plastic additives and industrial waste are quietly destabilising ecosystems.  iStock
Wildlife & Biodiversity

A four-step approach could help detect ecosystem collapse from hidden chemical pollution

With over 350,000 synthetic chemicals in use and production set to triple by 2050, researchers propose a four-step framework using eDNA, AI, and remote sensing to detect early warning signs of ecological distress

Gargi Gaur

  • Over 350,000 synthetic chemicals registered worldwide; production expected to triple by 2050

  • Pollution identified as main extinction driver for many threatened species

  • Framework proposes early warning tools using eDNA, AI and remote sensing

  • Researchers urge regulatory reform and real-time monitoring integration

  • Caution raised over model limitations, data gaps and local adaptability

Low-level chemical pollution is now putting nearly 20 per cent of endangered species at risk, and for many, it is the leading cause of decline, a new study has found. Since 1950, the world has seen a 50-fold increase in chemical production. With over 350,000 synthetic chemicals in use and production expected to triple by 2050 compared to 2010, researchers say the ecological fallout is accelerating unnoticed.

Published on June 25, 2025 in the journal Environmental Science and Ecotechnology, the study revealed that the cumulative effects of chemical pollutants such as trace pesticides, pharmaceutical residues, plastic additives and industrial waste are quietly destabilising ecosystems. Even when present in minute quantities, these substances can interact with climate change, habitat degradation and water stress to push ecosystems past tipping points.

“Our current models are too simplistic to capture how real ecosystems respond to pollution,” explained Xiaowei Jin, corresponding author and senior researcher at the China National Environmental Monitoring Centre, in a statement. “Chemical pollutants don't act alone — they interact with climate shifts, habitat loss and species dynamics.”

Framework for early intervention

To address this, a research team from institutions in China and the UK has proposed a four-part framework to detect early warning signs of ecological distress and prevent biodiversity collapse. The team includes experts from the Chinese Research Academy of Environmental Sciences, Beijing Normal University, the Chinese Academy of Sciences, Yunnan University and the United Kingdom Centre for Ecology and Hydrology.

Their proposed system includes:

  1. High-resolution ecological monitoring using tools such as environmental DNA (eDNA) sampling and chemical fingerprinting. In Guangzhou’s Chebei Stream, scientists were able to trace pollution to its origin using these technologies.

  2. Predictive analytics and AI, including machine learning and high-throughput toxicity testing, to identify early signs of stress before ecosystems reach a point of no return.

  3. Regulatory reform that incorporates real-time data into environmental decision-making. The European Union’s REACH programme, for example, could be enhanced to include dynamic monitoring and updated toxicity thresholds.

  4. Scalable detection technology, such as biosensors and satellite imagery, to monitor large-scale ecological shifts. In the Amazon, satellite data have already revealed slower forest recovery following drought—an early indicator of long-term disruption.

Together, these four steps offer a new way to protect biodiversity by acting early, before damage becomes permanent, and also bring together experts from different fields, like ecologists, data scientists, and policymakers, to work as a team to protect biodiversity.

Not a silver bullet

While the study marks a significant advance in linking pollution to biodiversity loss, the authors stress that these tools must be used cautiously. Early warning models, they note, can produce false positives or miss subtle but important ecological changes. Moreover, they depend on consistent, high-quality data — which is lacking in many parts of the world.

“By integrating high-resolution monitoring with predictive analytics, we can spot danger before collapse occurs. This new framework marks a vital turning point for environmental policy — one that better matches the complexity of the world we live in,” Jin said in a statement.

These findings come amid renewed international focus on pollution reduction under Target 7 of the Kunming-Montreal Global Biodiversity Framework, which calls for curbing pollution to levels not harmful to biodiversity by 2030.

As the pace of chemical production accelerates and the number of synthetic compounds in circulation rises, scientists warn that inaction could mean more silent collapses — ecosystems pushed past the brink not by chainsaws or rising heat, but by invisible toxins seeping into water, soil and air.