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| Author(s): |
Paulo Vinicius Ferraz Correa
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto Oceanográfico (IO/DIDC) |
| Defense date: | 2022-06-23 |
| Examining board members: |
Paulo Yukio Gomes Sumida;
Angelo Fraga Bernardino;
Abilio Soares Gomes;
José Angel Alvarez Perez
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| Advisor: | Paulo Yukio Gomes Sumida |
| Abstract | |
The Rio Grande Rise (RGR) is a region of commercial and scientific interest due to its potential for mining rare-earth elements (REEs). The application and demand for REEs have expanded over the years, especially with the use of renewable energy (such as wind farms, solar panels, and batteries). In this scenario, the RGR has gained attention from researchers, the Brazilian government, and other states due to its large potential for the exploitation of ferromanganese (Fe-Mn) crusts, which are a source of REEs. Unlike terrestrial mining, there are effectively no precedents for mineral exploitation in the deep sea. This thesis aims to characterize the RGR fauna and examine potential drivers for community structure and species distribution. A review of the literature and the OBIS and GBIF databases showed there is little information about the fauna and ecology in RGR. To help fill in these gaps, biological samples from rock dredges, seabed videos, and bathymetric data from RGR were collected in the MARINE E-TECH Project from two cruises with the vessels N/Oc. Alpha Crucis and RSS Discovery in 2018 and analyzed in this thesis. A diverse fauna was observed, with a higher abundance of sponges, corals, annelids, barnacles, and tube-dwelling amphipods, and 30% of the specimens found associated with larger organisms. Seabed videos revealed highly heterogeneous and rapidly changing habitats in RGR. The habitats formed by Fe-Mn deposits were dominated by distinct communities, which were rarely observed elsewhere. We found variations in the community structure at regional scales, with distinct communities on each side of the rift and at the southwest of the study area. Machine learning and regression models were used to predict the distribution of Sarostegia oculata, a branched hexactinellid that forms sponge gardens in Fe-Mn crusts. The models had excellent or good performance statistics and a high discrimination power between presence and absence sites. The main drivers for the distribution were depth, fine scale Bathymetric Position Index, and northness. Models predicted a high likelihood of S. oculata along with the rift borders with a low degree of uncertainty. Understanding the potential ecosystem impact is critical to any prospect of deep-sea mineral deposits becoming a potentially viable source of REEs. The results presented here will be of interest to all the stakeholders in the proposed mining activities and will facilitate more informed decision-making regarding these activities. (AU) | |
| FAPESP's process: | 17/11884-8 - Structure and Ecology of benthic communities of the Rio Grande Rise and their conservation for future deep-sea mining |
| Grantee: | Paulo Vinicius Ferraz Corrêa |
| Support Opportunities: | Scholarships in Brazil - Doctorate |