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| Natura: | Artículo científico |
| Lingua: | en |
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Scientific data
2025
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| Accesso online: | https://pubmed.ncbi.nlm.nih.gov/40483280/ |
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| _version_ | 1868266193691869184 |
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| author | Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure |
| author_facet | Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure |
| collection | PubMed - marine biology |
| contents | A macrozoobenthic data set of the Black Sea northwestern shelf. Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure Black Sea Biodiversity Ecosystem Aquatic Organisms Animals Benthic ecological data are crucial to study and manage ecosystems. On the one hand, abiotic and species data provide complementary information to identify habitats. On the other hand, trait data, describing taxon characteristics, are required to predict anthropogenic impacts on marine ecosystems. Indeed, species traits are now widely used to understand natural selection in communities or to highlight ecosystem functions. While trait data are in growing demand, compiling them is challenging, time-consuming and there are no properly established procedures for major marine ecosystems. Here, we share a data set comprising macrozoobenthic occurrences for 215 taxa over the Black Sea northwestern shelf, between 1995 and 2017, and 27 traits documented for 127 taxa that related to life cycle and ecosystem function. In addition, we provide an abiotic data set of physical and chemical variables generated by a model or compiled from in-situ data. This data set aims to fill the functional knowledge gap in the Black Sea and offers research opportunities to future studies covering ecosystem functions, biodiversity conservation, and management. |
| format | Artículo científico |
| id | pubmed_40483280 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Scientific data |
| record_format | pubmed |
| spellingShingle | A macrozoobenthic data set of the Black Sea northwestern shelf. Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure Black Sea Biodiversity Ecosystem Aquatic Organisms Animals A macrozoobenthic data set of the Black Sea northwestern shelf. Chevalier, Séverine Beauchard, Olivier Teacă, Adrian Begun, Tatiana Todorova, Valentina Vandenbulcke, Luc Soetaert, Karline Grégoire, Marilaure Black Sea Biodiversity Ecosystem Aquatic Organisms Animals Benthic ecological data are crucial to study and manage ecosystems. On the one hand, abiotic and species data provide complementary information to identify habitats. On the other hand, trait data, describing taxon characteristics, are required to predict anthropogenic impacts on marine ecosystems. Indeed, species traits are now widely used to understand natural selection in communities or to highlight ecosystem functions. While trait data are in growing demand, compiling them is challenging, time-consuming and there are no properly established procedures for major marine ecosystems. Here, we share a data set comprising macrozoobenthic occurrences for 215 taxa over the Black Sea northwestern shelf, between 1995 and 2017, and 27 traits documented for 127 taxa that related to life cycle and ecosystem function. In addition, we provide an abiotic data set of physical and chemical variables generated by a model or compiled from in-situ data. This data set aims to fill the functional knowledge gap in the Black Sea and offers research opportunities to future studies covering ecosystem functions, biodiversity conservation, and management. |
| title | A macrozoobenthic data set of the Black Sea northwestern shelf. |
| topic | Black Sea Biodiversity Ecosystem Aquatic Organisms Animals |
| url | https://pubmed.ncbi.nlm.nih.gov/40483280/ |