TRANSFER
Keys to understanding the transfer of atmospheric fluctuations to the dynamics of lake plankton
The foot print of global change shows up in multiple indicators. As evidence accumulates, some paradoxes also emerge. At multiannual time scales, one intriguing aspect is why some ecosystems seem to follow more closely indicators of the general atmospheric dynamics (e.g., CO2 increase, hemispheric mean annual temperature) than the local weather and deposition records. Pathways of mechanistic causality must exist that explain the apparent paradox. Probably, they are related to processes of different characteristic reaction, and renewal times. One of the systems in which the phenomenon has been observed is the plankton of remote lakes. This case is excellent to address the issue.
The planktonic system, which is very reactive and thus potentially able to follow closely the atmospheric fluctuations, is also influenced by two major reservoirs of materials and long residence time: lake sediments and groundwater compartments in the catchment.
This project has the general objective to understand the link between the atmospheric, and planktonic dynamics and to what extent it depends on processes in the lake itself (subproject 1) and processes in the catchment (subproject 2). The questions will be addressed with case studies and numerical simulations. The central Pyrenees are the experimental location, in particular Lake Redon and the watershed of the Ribera de St. Nicolau in the National Park of Aigüestortes i Estany de Sant Maurici.
A collection of analytical (e.g., stable isotopes, molecular markers) and numerical techniques will be applied to studies that include:
- Mesocosms experiments
- Multiannual time series of planktonic, biogeochemical and weather data
- High-resolution sediment cores
- Groundwater compartments and their reactivity
- Modeling of the transport from the basin to the lakes
- Modeling of the coupling between atmosphere and sediment at multiannual scales
- Modelling of the planktonic dynamics as a metabolic network