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Marine fish and benthic biota before the 2019 oil spill: A baseline dataset for monitoring programs and impact assessments at Rio Grande Norte state, Northeastern Brazil
Abstract In 2019 an oil spill spread over more than 4000 km of the Brazilian coastline. Monitoring programs that allow for the evaluation of potential impacts on communities and ecosystems and their recovery through time are needed and rely on baseline information previous to the oil spill. Here we...
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Published in: | Anais da Academia Brasileira de Ciências 2022-01, Vol.94 (suppl 2), p.e20210536-e20210536 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Abstract In 2019 an oil spill spread over more than 4000 km of the Brazilian coastline. Monitoring programs that allow for the evaluation of potential impacts on communities and ecosystems and their recovery through time are needed and rely on baseline information previous to the oil spill. Here we compiled qualitative and quantitative data available from 8 studies on fish and benthic species from different habitats of Rio Grande do Norte (RN) from 2007 to 2018. We assessed the number of species from different locations and compiled information on conservation status and human use. We mapped the study areas and habitats and overlapped them with those affected by the oil spill. The RN state has a high diversity of fish (175 species) and benthic species (285 species), of which more than half of fish (52%) and 2% of benthic species are threatened and 72,8% of fish and 7,9% of benthic species are of commercial interest. Information of most habitats is still poorly known (i.e.majority ofthe available data are from unique and punctual sampling), which may weaken future evaluations of the real impact of the oil spill. Nonetheless, it is possible to design reliable monitoring based on our dataset, persistent contamination and future loss of diversity. |
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ISSN: | 0001-3765 1678-2690 1678-2690 |
DOI: | 10.1590/0001-3765202120210536 |