The foraminiferal response to climate stressors project: tracking the community response of planktonic foraminifera to historical climate change
de Garidel-Thoron, T.; Chaabane, S.; Giraud, X.; Meilland, J.; Jonkers, L.; Kucera, M.; Brummer, G.-J. A.; Grigoratou, M.; Monteiro, F.M.; Greco, M.; Mortyn, P.G.; Kuroyanagi, A.; Howa, H.; Beaugrand, G.; Schiebel, R. (2022). The foraminiferal response to climate stressors project: tracking the community response of planktonic foraminifera to historical climate change. Front. Mar. Sci. 9: 827962. https://dx.doi.org/10.3389/fmars.2022.827962
In: Frontiers in Marine Science. Frontiers Media: Lausanne. e-ISSN 2296-7745, meer
|   |
| Trefwoorden |
Foraminifera [WoRMS]
Marien/Kust |
| Author keywords |
plankton; foraminifera; global warming; ocean acidification; biodiversity |
| Auteurs | | Top |
- de Garidel-Thoron, T.
- Chaabane, S.
- Giraud, X.
- Meilland, J.
- Jonkers, L.
|
- Kucera, M.
- Brummer, G.-J. A., meer
- Grigoratou, M.
- Monteiro, F.M.
- Greco, M.
|
- Mortyn, P.G.
- Kuroyanagi, A.
- Howa, H.
- Beaugrand, G., meer
- Schiebel, R.
|
| Abstract |
Planktonic Foraminifera are ubiquitous marine protozoa inhabiting the upper ocean. During life, they secrete calcareous shells, which accumulate in marine sediments, providing a geological record of past spatial and temporal changes in their community structure. As a result, they provide the opportunity to analyze both current and historical patterns of species distribution and community turnover in this plankton group on a global scale. The FORCIS project aims to unlock this potential by synthesizing a comprehensive global database of abundance and diversity observations of living planktonic Foraminifera in the upper ocean over more than 100 years starting from 1910. The database will allow for unravelling the impact of multiple global-change stressors acting on planktonic Foraminifera in historical times, using an approach that combines statistical analysis of temporal diversity changes in response to environmental changes with numerical modeling of species response based on their ecological traits. |
|
