Impact modelling

REPORT: Assessing the quantitative risk of seafloor polymetallic nodule mining on ecosystem indicators

• Deep-sea mining causes measurable changes to key seafloor species groups, with some showing signs of recovery over time, while others remain highly impacted.
• A new risk model helps predict how different species groups respond to mining, using real-world data and expert knowledge to improve accuracy.
• The study provides a science-based method to guide environmental limits and monitoring, helping decision-makers understand where and when mining might cause serious harm.

This report presents a detailed study on how deep-sea mining affects marine life on the seafloor. The focus is on the NORI-D lease area in the Clarion-Clipperton Zone (CCZ), a region targeted for mining polymetallic nodules. These nodules contain valuable metals, but the ecosystems they support are poorly understood.

One of the key strengths of the study is its use of real-world data collected by multiple research teams, including those funded through this project. The data was independently analysed by the CSIRO Research Consortium, ensuring transparency and scientific integrity.

To assess the risks, scientists developed a model that predicts how different groups of seafloor animals—like deposit feeders, predators, and suspension feeders—respond to mining. The model uses data from before and after test mining activities, combined with data from previous scientific studies. It also includes a way to update predictions if new monitoring data becomes available.

The researchers grouped species into five main types based on how they live and feed. They used Bayesian models to estimate how each group is likely to be affected by mining, and how long recovery might take. The model uses survey data to understand and predict how species abundances will change post mining.

Some groups showed very little recovery, while others were able to recover from mining impacts faster. Sessile suspension feeders, which include animals that attach to the seafloor and filter food from the water, were found to be the most vulnerable. These species showed the greatest decline in abundance after mining and the slowest signs of recovery.

In contrast, mobile epifaunal carnivores—species that move across the seafloor and feed on other animals—were more resilient. These animals showed quicker recovery but had not recovered back to pre-mining densities after 1 year.   Interestingly, the study also found that some areas outside the direct mining tracks, particularly those affected only by sediment plumes, showed little to no change in certain species groups. This suggests that while direct disturbance has clear impacts, the effects of nearby sedimentation will vary between species.

The data used in this model is from a limited test mining operation, which may not be reflective of the impacts of an industrial scale operation and caution would be need if extrapolated to a larger scale operation. Overall, the study provides a robust, science-based tool to help regulators and stakeholders make informed decisions about deep-sea mining, with a strong focus on protecting marine ecosystems.