Objective
Climate change is a threat to ecosystems, both aquatic and terrestrial. Shallow lakes are aquatic systems of global importance for their economic, amenity and biodiversity values. They seem to exist in one of two alternative states, both of which are resistant to change due to multiple buffering mechanisms. Much research has gone into elucidating under what conditions and how will these mechanisms be overcome as a result of climate change. However, the results obtained have provided little information about the potential responses to climate change under intermediate nutrient regimes and most probable warming scenarios.
The zooplankton is a key link in trophic cascades of shallow lakes, since they provide the food base of fish through planktivory, and the limit to phytoplankton crops, through herbivory. Shifts from a clear to a turbid state in shallow lakes typically involve an increase or decrease in their capacity to control algal biomass and therefore water transparency. This pivotal role of zooplankton could be affected by global warming, with cascading effects on algal dominance and lake ecosystem state. Specifically, global warming may influence the survival and feeding strategies of the zooplankton in shallow lakes.
The present proposal aims to examine zooplankton-related processes behind the switch to turbid conditions in shallow lakes occurring in response to global warming through the study of their survival and feeding strategies. A combination of empirical and mechanistic approaches will be used, through inter-seasonal variations and time series analyses of contemporary data, novel stable isotope analyses of zooplankton populations and their egg banks and mesocosms experiments. In these, zooplankton population dynamics and feeding activities will be examined under nutrient and fish treatments in novel flow-through warmed mesocosms mimicking global warming trends.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdatabases
- natural sciencesbiological sciencesmicrobiologyphycology
- natural sciencesbiological sciencesecologyecosystems
- natural sciencesbiological sciencesbiological behavioural sciencesethologybiological interactions
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
Keywords
Call for proposal
FP6-2005-MOBILITY-5
See other projects for this call
Funding Scheme
EIF - Marie Curie actions-Intra-European FellowshipsCoordinator
AARHUS C
Denmark