Causal Approach to Determining the Environmental Risks of Seabed Mining

Laura Kaikkonen*, Inari Helle, Kirsi Kostamo, Sakari Kuikka, Anna Törnroos, Henrik Nygård, Riikka Venesjärvi, Laura Uusitalo

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
25 Downloads (Pure)


Mineral deposits containing commercially exploitable metals are of interest for seabed mineral extraction in both the deep sea and shallow sea areas. However, the development of seafloor mining is underpinned by high uncertainties on the implementation of the activities and their consequences for the environment. To avoid unbridled expansion of maritime activities, the environmental risks of new types of activities should be carefully evaluated prior to permitting them, yet observational data on the impacts is mostly missing. Here, we examine the environmental risks of seabed mining using a causal, probabilistic network approach. Drawing on a series of expert interviews, we outline the cause-effect pathways related to seabed mining activities to inform quantitative risk assessments. The approach consists of (1) iterative model building with experts to identify the causal connections between seabed mining activities and the affected ecosystem components and (2) quantitative probabilistic modeling. We demonstrate the approach in the Baltic Sea, where seabed mining been has tested and the ecosystem is well studied. The model is used to provide estimates of mortality of benthic fauna under alternative mining scenarios, offering a quantitative means to highlight the uncertainties around the impacts of mining. We further outline requirements for operationalizing quantitative risk assessments in data-poor cases, highlighting the importance of a predictive approach to risk identification. The model can be used to support permitting processes by providing a more comprehensive description of the potential environmental impacts of seabed resource use, allowing iterative updating of the model as new information becomes available.

Original languageEnglish
Pages (from-to)8502-8513
Number of pages12
JournalEnvironmental Science and Technology
Issue number13
Publication statusPublished - 6 Jul 2021
MoE publication typeA1 Journal article-refereed


  • Bayesian networks
  • causal maps
  • ecological risk assessment
  • expert elicitation
  • multiple pressures
  • probabilistic modeling
  • seabed mining


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