The role of rapid environmental assessment in monitoring the environmental impacts of deep-sea mining
Tilot, V.; Aarab, N.; Navas, J.M.; Dahl, A.; de Grissac, A.J. (2025). The role of rapid environmental assessment in monitoring the environmental impacts of deep-sea mining, in: Sharma, R. (Ed.) Deep-sea mining management, policy and regulation: Data management, environmental monitoring, techno-economic assessment, Law of the Sea and regulatory regimes. pp. 257-323. https://dx.doi.org/10.1007/978-3-031-92737-9_9
In: Sharma, R. (Ed.) (2025). Deep-sea mining management, policy and regulation: Data management, environmental monitoring, techno-economic assessment, Law of the Sea and regulatory regimes. Springer: Cham. ISBN 978-3-031-92736-2. XIII, 525 pp. https://dx.doi.org/10.1007/978-3-031-92737-9, more
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| Authors | | Top |
- Tilot, V., more
- Aarab, N.
- Navas, J.M.
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- Dahl, A.
- de Grissac, A.J.
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| Abstract |
We here consider the extent to which Rapid Environmental (or Ecological) Assessment (REA) can be applied to the deep-sea benthic environment and the associated water column as a tool for surveying very large areas to assess the risk of environmental impact from deep-sea mining. In particular, we propose that REA could be conducted more widely through video and still imagery collected by the various platforms employed in benthic and pelagic studies. REA protocols, as developed for the assessment of large areas of shallow-water marine habitat, and used on land, have in common that they accept semi-quantitative estimates of the abundances of biological taxa and of the strength of environmental factors, these often being assessed on a predefined 5-, 6-, or 10-point scale. REAs also accept taxonomic identification limited to higher taxonomic levels or even morphospecies level and may restrict identification to preselected orders or families, focusing on indicator and sentinel species, preferential habitats, and trait-based indicators. While estimates of abundance may be made with lower accuracy than achievable given unlimited resources, REA allows much greater areas to be monitored and can result in greater precision and statistical sensitivity if it results in much greater numbers of replicate samples being processed. Metrics of biodiversity such as taxonomic distinctiveness can also be applied to the data, as can indices of environmental sensitivity which, when combined with monitoring of indicator taxa, can be used to provide a traffic-light system indicative of ecosystem health. REA, relying on imaging, is proposed to be used in conjunction with operational oceanographic systems covering the entire water column and other emerging technologies, such as environmental DNA, acoustics, bioluminescence monitoring, multi-parametric satellite tagging, and hydrodynamic modelling, that may prove effective for monitoring extensive ocean areas in the face of environmental change. With the progress of machine learning to manage large datasets of taxa, habitat identification and oceanographic concepts developed by experts, annotation efforts can be facilitated, datasets formatted and standardised, and models developed. We also highlight the potential role that citizen scientists/volunteers and indigenous peoples can play in REA if adequate training is provided and well-constructed protocols are available. The necessity of in situ long-term multi-parametric observation platforms is highlighted as is the standardisation of REA worldwide, enabling comparisons and joint management decisions as oceanographic processes occur on regional scales. |
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