Summary
One of the most pressing scientific challenges today is understanding the fate of our oceans and marine ecosystems under on-going climate change. Unfortunately, anthropogenic stressors act at a rate and magnitude that exceed recent natural variability, making the use of decadal ecological data and time-series insufficient for predictions of future behaviour of marine ecosystems. MICRO2MACRO will reconstruct snapshots of marine pelagic ecosystems between 54 and 32 million years ago (Eocene and early Oligocene), when climate and environmental conditions approximated what we will start to experience in the next century and beyond. Using the microfossil record of planktonic foraminifera (PF), the most complete of any Cenozoic eukaryote, the project will generate the first methodologically controlled (hence reproducible) early Cenozoic global dataset of ecology, abundance, species composition, diversity and biogeography (macroecology) of these prolific pelagic calcifiers. Benefiting from the mole of data generated over the last 15 years, I will learn and apply novel tools in data-science technology to compile ocean temperature and chemistry datasets for the studied time intervals and statistically compare them against the new PF dataset generated with this project. This study will combine the most advanced knowledge in several disciplines (micropaleontology, informatics, statistical ecology) to test for links between time-specific climate (e.g., sea surface temperatures) and ecosystem (e.g., species composition, dominant ecology) configurations, and understand how plankton biogeography was shaped in a warmer world. Hence, MICRO2MACRO will highlight future ecological and evolutionary analogues if the current climate trajectory remains interrupted and we are to hit climate conditions similar to those in the Eocene and Oligocene. Given the uncertainties associated with projections based on modern data this study will represent a major advancement in the field.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101019438 |
| Start date: | 01-09-2022 |
| End date: | 31-08-2024 |
| Total budget - Public funding: | 162 806,40 Euro - 162 806,00 Euro |
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Original description
One of the most pressing scientific challenges today is understanding the fate of our oceans and marine ecosystems under on-going climate change. Unfortunately, anthropogenic stressors act at a rate and magnitude that exceed recent natural variability, making the use of decadal ecological data and time-series insufficient for predictions of future behaviour of marine ecosystems. MICRO2MACRO will reconstruct snapshots of marine pelagic ecosystems between 54 and 32 million years ago (Eocene and early Oligocene), when climate and environmental conditions approximated what we will start to experience in the next century and beyond. Using the microfossil record of planktonic foraminifera (PF), the most complete of any Cenozoic eukaryote, the project will generate the first methodologically controlled (hence reproducible) early Cenozoic global dataset of ecology, abundance, species composition, diversity and biogeography (macroecology) of these prolific pelagic calcifiers. Benefiting from the mole of data generated over the last 15 years, I will learn and apply novel tools in data-science technology to compile ocean temperature and chemistry datasets for the studied time intervals and statistically compare them against the new PF dataset generated with this project. This study will combine the most advanced knowledge in several disciplines (micropaleontology, informatics, statistical ecology) to test for links between time-specific climate (e.g., sea surface temperatures) and ecosystem (e.g., species composition, dominant ecology) configurations, and understand how plankton biogeography was shaped in a warmer world. Hence, MICRO2MACRO will highlight future ecological and evolutionary analogues if the current climate trajectory remains interrupted and we are to hit climate conditions similar to those in the Eocene and Oligocene. Given the uncertainties associated with projections based on modern data this study will represent a major advancement in the field.Status
SIGNEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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